Construction and methods of use of a therapeutic cancer vaccine library comprising fusion-specific vaccines

ABSTRACT

Methods described herein relate to constructing therapeutic fusion-specific vaccine libraries, selecting a therapeutic fusion-specific vaccine for a cancer patient, and/or constructing a de novo therapeutic fusion-specific vaccine for patients having a gene fusion that is absent from a fusion-specific vaccine library.

RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. § 119(e) of the filing date of U.S. provisional patent application Ser. No. 62/319,774, entitled “CONSTRUCTION AND METHODS OF USE OF A THERAPEUTIC CANCER VACCINE LIBRARY COMPRISING FUSION-SPECIFIC VACCINES,” filed Apr. 7, 2016, the entire contents of which are incorporated herein by reference.

FIELD OF THE INVENTION

The methods described herein are directed toward the field of immunotherapy for cancer patients.

BACKGROUND

Recent advances in personalized genomic sequencing and cancer genomic sequencing technologies have made it possible to obtain patient-specific information. This information can be used to prepare patient-specific medicines including patient-specific cancer vaccines that are developed based on the genome of the patient and the mutation information gathered from the patient's biological sample.

SUMMARY

Provided herein, inter alia, are methods for constructing therapeutic fusion-specific vaccine libraries, selecting a therapeutic fusion-specific vaccine for a cancer patient, and/or constructing a de novo therapeutic fusion-specific vaccine for patients having a gene fusion that is absent from a fusion-specific vaccine library.

In some embodiments, the method provides compositions for providing therapeutic fusion-specific vaccine libraries that can be used as sources of vaccines for many cancer patients.

In some aspects, the specification provides a method for constructing a therapeutic fusion-specific vaccine library for a cancer patient, the method comprising (a) identifying one or more tumor-specific gene fusions from publicly available data, (b) identifying one or more fusion junction sequences, wherein the fusion junction sequences comprise nucleic acid sequences and/or amino acid sequences corresponding to one or more tumor-specific gene fusions, (c) obtaining information relating to interaction between fusion junction sequences with one or more HLA alleles, and (d) selecting at least one fusion junction sequence for the therapeutic fusion-specific vaccine library.

In some aspects, the specification provides a method for selecting a therapeutic fusion-specific vaccine for a cancer patient, the method comprising (a) determining the presence of one or more tumor-specific gene fusions in a biological sample from the cancer patient, (b) obtaining information relating to one or more HLA alleles of the cancer patient, (c) analyzing a library of fusion-specific vaccines, wherein each fusion-specific vaccine in the library comprises one or more fusion junction sequences having a nucleic acid sequences and/or an amino acid sequence corresponding to one or more tumor-specific gene fusions, and (d) selecting at least one fusion-specific vaccine in the library as the therapeutic fusion-specific vaccine for the cancer patient by selecting the fusion-specific vaccine comprising (i) one or more fusion junction sequences corresponding to one or more tumor-specific gene fusions of the cancer patient, and (ii) one or more fusion junction sequences that bind one or more HLA alleles of the cancer patient.

In some aspects, the specification provides a method for constructing a de novo therapeutic fusion-specific vaccine for a cancer patient, the method comprising (a) determining the presence of one or more tumor-specific gene fusions in a biological sample from the cancer patient, (b) obtaining information relating to one or more HLA alleles of the cancer patient, (c) determining that the cancer patient's fusion junction sequence is not present in the library of fusion-specific vaccines, and (d) constructing at least one fusion-specific vaccine as the de novo therapeutic fusion-specific vaccine for the cancer patient by constructing the fusion-specific vaccine comprising (i) one or more fusion junction sequences corresponding to one or more tumor-specific gene fusions of the cancer patient, and (ii) one or more fusion junction sequences that bind one or more HLA alleles of the cancer patient.

In some embodiments, the method further comprises administering the therapeutic fusion-specific vaccine to the cancer patient.

In some embodiments, the biological sample is a tissue sample or fluid sample taken from the cancer patient. In some embodiments, the biological sample is analyzed by DNA sequencing, RNA sequencing, and/or protein sequencing. In some embodiments, one or more tumor-specific gene fusions are identified in the biological sample. In some embodiments, information relating to one or more HLA alleles of the cancer patient are obtained by analysis of the biological sample.

In some embodiments, the fusion-specific vaccine comprises one or more nucleic acid sequences corresponding to one or more tumor-specific gene fusions. In some embodiments, the fusion-specific vaccine comprises one or more peptides having amino acid sequences corresponding to one or more tumor-specific gene fusions. In some embodiments, the fusion-specific vaccine comprises one or more peptides selected from Table A.

In some embodiments, the fusion-specific vaccine comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 peptides corresponding to one or more tumor-specific gene fusions. In some embodiments, the fusion-specific vaccine comprises 20 or more peptides corresponding to one or more tumor-specific gene fusions.

In some embodiments, the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC₅₀ less than 500 nM. In some embodiments, the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC₅₀ less than 250 nM. In some embodiments, the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC₅₀ less than 100 nM. In some embodiments, the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC₅₀ less than 50 nM.

In some embodiments, the library of fusion-specific vaccines comprises at least 2-10 fusion-specific vaccines having distinct fusion junction sequences. In some embodiments, the library of fusion-specific vaccines comprises at least 5-10 fusion-specific vaccines corresponding to distinct fusion junction sequences. In some embodiments, the library of fusion-specific vaccines comprises at least 10-50 fusion-specific vaccines corresponding to distinct fusion junction sequences. In some embodiments, the library of fusion-specific vaccines comprises at least 50-100 fusion-specific vaccines corresponding to distinct fusion junction sequences. In some embodiments, the library of fusion-specific vaccines comprises 100 or more fusion-specific vaccines corresponding to distinct fusion junction sequences.

In some embodiments, the fusion-specific vaccine comprises one or more peptides having 8-10 amino acids. In some embodiments, the fusion-specific vaccine comprises one or more peptides having 10-25 amino acids. In some embodiments, the fusion-specific vaccine comprises one or more peptides having 25-50 amino acids. In some embodiments, the fusion-specific vaccine comprises one or more peptides having 50-100 amino acids. In some embodiments, the fusion-specific vaccine comprises one or more peptides having 100 or more amino acids. In some embodiments, the fusion-specific vaccine comprises a combination of two or more peptides having numbers of amino acids described herein.

In some embodiments, the fusion-specific vaccine comprises one or more peptides having an amino acid sequence corresponding to a one or more tumor-specific gene fusions and one or more addition amino acid sequences. In some embodiments, the fusion-specific vaccine comprises two or more peptides having an amino acid sequence corresponding to two or more tumor-specific gene fusions and one or more addition amino acid sequences.

In some embodiments, the fusion-specific vaccine comprises one or more peptides having a modification. In some embodiments, the fusion-specific vaccine comprises one or more adjuvants. In some embodiments, the fusion-specific vaccine comprises the peptide having a concentration of 100 ng-10 mg.

In some embodiments, the fusion-specific vaccine is administered once to the cancer patient. In some embodiments, the cancer patient is treated with two or more doses of the fusion-specific vaccine.

In some embodiments, the library of fusion-specific vaccines comprises peptides having an amino acid sequence corresponding to gene fusions that are present in a type of cancer. In some embodiments, the type of cancer is melanoma, skin cancer, head and neck cancer, breast cancer, lung cancer, ovarian cancer, cervical cancer, prostate cancer, thyroid cancer, kidney cancer, liver cancer, pancreatic cancer, gastric cancer, testicular cancer, brain tumor, glioma, glioblastoma, solitary fibrous tumor, bladder cancer, colorectal cancer, renal cell carcinoma, sarcoma, myeloma, leukemia, and/or lymphoma. In some embodiments, the type of cancer is a metastatic tumor. In some embodiments, the type of cancer is any tumor type.

In some embodiments, the cancer patient is administered dendritic cells or other antigen presenting cells that have been pulsed with at least one fusion junction peptide having a sequence from the fusion-specific vaccine library. In some embodiments, the cancer patient is administered dendritic cells or other antigen presenting cells comprising at least one fusion junction peptide having a sequence from the fusion-specific vaccine library. In some embodiments, autologous T-cells can be collected from the cancer patient, stimulated ex vivo with fusion junction sequences, and stimulated autologous T-cells are transfused into the cancer patient.

BRIEF DESCRIPTION OF DRAWINGS

The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present disclosure, which can be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.

FIG. 1 illustrates a non-limiting example of a typical strategy for generating personalized neoantigenic vaccines including 3 steps: (1) detection of mutations from sequencing data and mutation calling; (2) identification of personal neoantigens; and (3) vaccine composition.

FIG. 2 illustrates a non-limiting example of a strategy for constructing a vaccine library comprising (1) screening of publicly available databases containing cancer sample sequences, information relating to genomic aberrations in cancer, and/or information relating to gene fusions in cancer; (2) extracting gene fusion incidence data; (3) analyzing fusion breakpoint peptides and MHC interaction; (4) selecting fusion breakpoint peptides based on affinity for MHC proteins; (5) calculating population coverage of selected peptides; and (6) incorporation of selected peptides into vaccine library.

FIG. 3 illustrates a non-limiting scheme for selecting patients for treatment with a vaccine library comprising (1) examining patient's cancer genome for gene fusions; (2) determining patient's HLA genotype; (3) matching vaccine library to patient's gene fusion and HLA type, and (4) administering a vaccine from the vaccine library to the patient or de novo vaccine construction from the patient's tumor specific mutations or selection of another treatment.

FIG. 4 shows a non-limiting example of a therapeutic cancer vaccine comprising BCR/ABL1 fusion peptides. The method described in the specification is applied to identification of BCR/ABL1 fusion peptides for the treatment of CML. Three breakpoints in BCR and ABL1 genes are marked with arrows (1). Fusion at these breakpoints yields two BCR/ABL1 gene fusions that are present in 90% of CML patients which comprises 45,000 patients in the U.S. and 950,00 patients worldwide (2). The method discloses two BCR/ABL1 fusion peptides selected based on allele coverage and patient coverage that are present in 68% of CML patients which means that 30,000 patients in the U.S. and 650,000 patients worldwide are eligible for treatment with a cancer vaccine comprising these two peptides (3). The sequences correspond to SEQ ID NOs: 610 to 611 from top to bottom, respectively.

FIG. 5 shows a non-limiting example of an environment in which embodiments of the present methods may operate.

FIG. 6 shows a non-limiting example of a data structure for storing data associated with one or more patients, in accordance with some embodiments of the present methods.

FIG. 7 shows flow chart of an illustrative process for matching patient data and library data, in accordance with some embodiments of the present methods.

FIG. 8 shows a block diagram of an illustrative computer system that may be used in implementing aspects of the present methods.

DETAILED DESCRIPTION

Applicant has recognized that patient-specific medicines, such as patient-specific vaccines, although effective, can be very expensive. As illustrated in FIG. 1, generating a patient specific vaccine typically involves a series of steps that are tailored for each individual patient, including detecting mutations from patient sequence data, identifying patient-specific neoantigens, and designing and synthesizing a patient-specific vaccine composition. In contrast, Applicant has developed methods and compositions for providing simple vaccine libraries that can be used as sources of vaccines for many cancer patients. Applicant has recognized that many cancers involve gene fusions, regardless of whether the cancers also include point mutations or other genetic rearrangements. Applicant has developed a method involving a vaccine library comprising a plurality of fusion junction sequences corresponding to the protein products of gene fusions associated with cancers in many patients. Aspects of the application are based, at least in part, on the recognition that gene fusions are present in many cancers and that a library of fusion-specific vaccines can be generated to represent a significant percentage of cancers without requiring de novo construction of personalized cancer vaccines for patients having cancers associated with these gene fusions.

Accordingly, aspects of the application relate to methods and compositions for providing fusion-specific cancer vaccines to patients without resorting to personalized vaccine development for each patient. In some embodiments, a library of fusion-specific vaccines is provided and a patient is evaluated to determine whether the patient will be responsive to at least one of the vaccines in the library. In some embodiments, the presence of one or more cancer-associated gene fusions is identified in the patient. In some embodiments, the HLA genotype of the patient is evaluated to determine whether the patient will be responsive to one or more fusion-specific vaccines corresponding to a cancer-associated gene fusion identified in the patient. In some embodiments, if the patient is determined to be responsive to at least one fusion-specific vaccine in the library, then one or more of the vaccines is administered to the patient. In some embodiments, if the patient is determined not to be responsive to at least one fusion-specific vaccine in the library, then a personalized vaccine can be prepared de novo for the patient.

A Fusion-Specific Vaccine Library

In some aspects, the specification provides a method for constructing a therapeutic fusion-specific vaccine library for a cancer patient, including (a) identifying one or more tumor-specific gene fusions from publicly available data, (b) identifying one or more fusion junction sequences, wherein the fusion junction sequences comprise nucleic acid sequences and/or amino acid sequences corresponding to one or more tumor-specific gene fusions, (c) obtaining information relating to interaction between fusion junction sequences with one or more HLA alleles, and (d) selecting at least one fusion junction sequence for the therapeutic fusion-specific vaccine library. For example, FIG. 2 illustrates a non-limiting embodiment for constructing a vaccine library that includes screening publicly available databases containing cancer sample sequences, information relating to genomic aberrations in cancer, and/or information relating to gene fusions in cancer; extracting gene fusion incidence data; analyzing fusion breakpoint peptides and MHC interaction; selecting fusion breakpoint peptides based on affinity for MHC proteins; calculating population coverage of selected peptides; and incorporation of selected peptides into vaccine library. It should be appreciated that one or more of these steps may be omitted or modified depending on the vaccine library being developed. For example, sequence and related information can be obtained from any suitable source including public, private, customized, or other libraries containing cancer-related sequence information. In some embodiments, gene fusion incidence data does not need to be used. In some embodiments, population coverage does not need to be calculated. Accordingly, in some embodiments, a library can be designed by i) selecting fusion peptides of interest (e.g., based on one or more criteria, for example the types of cancer to be covered, the target patient population, the geographic region, the size and range of peptides to be included in the library, etc., or any combination thereof), and ii) obtaining or calculating MHC interaction information for those peptides. In some embodiments, the library can by synthesized or assembled using any suitable synthetic techniques (e.g., any suitable peptide chemistry, recombinant expression techniques, or any combination thereof).

In some aspects, the specification provides a method for selecting a therapeutic fusion-specific vaccine for a cancer patient, the method comprising (a) determining the presence of one or more tumor-specific gene fusions in a biological sample from the cancer patient, (b) obtaining information relating to one or more HLA alleles of the cancer patient, (c) analyzing a library of fusion-specific vaccines, wherein each fusion-specific vaccine in the library comprises one or more fusion junction sequences having a nucleic acid sequences and/or an amino acid sequence corresponding to one or more tumor-specific gene fusions, and (d) selecting at least one fusion-specific vaccine in the library as the therapeutic fusion-specific vaccine for the cancer patient by selecting the fusion-specific vaccine comprising (i) one or more fusion junction sequences corresponding to one or more tumor-specific gene fusions of the cancer patient, and (ii) one or more fusion junction sequences that bind one or more HLA alleles of the cancer patient. FIG. 3 illustrates a non-limiting example of a method of selecting a vaccine for a patient from a vaccine library described in this application. In some embodiments, i) a patient's cancer genome (e.g., the genome of a cancer in the patient, for example obtained from a biopsy or other sample obtained from cancer tissue in the patient) is analyzed to detect the presence of one or more gene fusions, ii) the patient's HLA genotype is determined (e.g., by sequencing one or more HLA loci of the patient, or obtained from whole genome sequence data for the patient, and iii) the library and the patient's HLA genotype are evaluated to determine with the library contains one or more peptides that match the patient's HLA genotype (e.g., based on one or more matching criteria that can be selected by the user, for example by a physician or a healthcare organization). If the library contains one or more peptides that are suitable for the patient (e.g., that correspond to one or more tumor specific mutations/neoantigens and that are HLA matched, for example based on specified HLA match criteria), then a vaccine containing one or more of those peptides can be selected from the library and administered to the patient. In the event that the library does not contain any peptides that are suitable for the patient (e.g., based on the tumor specific mutations in the patient that are not represented in the library and/or based on a failure to meet the specified HLA match criteria) then a de novo vaccine can be designed and synthesized for the patient (e.g., based on the patient's tumor specific mutations/neoantigens and/or HLA type) and/or a different therapy can be selected for the patient.

In some aspects, the specification provides a method for constructing a de novo therapeutic fusion-specific vaccine for a cancer patient, the method comprising (a) determining the presence of one or more tumor-specific gene fusions in a biological sample from the cancer patient, (b) obtaining information relating to one or more HLA alleles of the cancer patient, (c) determining that the cancer patient's fusion junction sequence is not present in the library of fusion-specific vaccines, and (d) constructing at least one fusion-specific vaccine as the de novo therapeutic fusion-specific vaccine for the cancer patient by constructing the fusion-specific vaccine comprising (i) one or more fusion junction sequences corresponding to one or more tumor-specific gene fusions of the cancer patient, and (ii) one or more fusion junction sequences that bind one or more HLA alleles of the cancer patient.

In some embodiments, the fusion-specific vaccine comprises one or more nucleic acid sequences corresponding to one or more tumor-specific gene fusions. In some embodiments, the fusion-specific vaccine comprises one or more peptides having amino acid sequences corresponding to one or more tumor-specific gene fusions. In some embodiments, the fusion-specific vaccine comprises one or more peptides selected from Table A. In some embodiments, one or more of the peptides listed in Table A is included in a peptide vaccine library. In some embodiments, one or more peptides in a peptide vaccine library consists of or includes a fragment of a peptide listed in Table A. In some embodiments, a fragment includes at least one amino acid (e.g., at least 2, 3, 4, 5 or more amino acids) from the N-terminal portion of a fusion peptide and at least one amino acid (e.g., at least 2, 3, 4, 5 or more amino acids) from the C-terminal portion of a fusion peptide. A vaccine library can include a plurality separate receptacles each containing a different peptide or a different combination of two or more peptides. Accordingly, a library can be a collection of receptacles, for example, wells, vials, tubes, or other containers capable of storing one or more different peptides, for example in the form of dry preparations (e.g., powder or crystalline form), liquid preparations (e.g., aqueous, organic, or other solutions), suspensions, or a combination thereof in different containers. In some embodiments, the receptacles are separate. In some embodiments, the receptacles are connected (e.g., in the form of an array, for example a 2D array). Receptacles can be made of any suitable material (e.g., glass, plastic, polymer, or other suitable material). In some embodiments, different peptides may be provided in different solutions (e.g., different salt concentrations, different pHs, etc.) depending on their solubility properties. Peptides in receptacles in a library can be provided at any suitable concentration (for example, nanomolar (e.g., from 1-1,000 nM), micromolar (e.g., from 1-1,000 μM), millimolar (e.g., 1-1,000 mM), or molar (e.g., 1M or higher)). Different peptides may be provided at different concentrations. In some embodiments, a peptide in a library is in a solution without an adjuvant or other agent, and an adjuvant or other agent may be added when the vaccine is prepared. However, in some embodiments, a peptide preparation in a library may also contain an adjuvant and/or other agent (e.g., a solubilizing or stabilizing agent, a therapeutic agent, or other agent).

Once a suitable combination of peptides has been determined or selected for a patient as described in this application, a vaccine can be prepared for the patient by retrieving (e.g., using a pipette or other suitable device for transferring the peptide(s)) from the appropriate library receptacles an appropriate amount of the one or more peptides that were identified to be suitable for that patient. The resulting combination of peptide(s) can be transferred to one or more suitable containers (e.g., syringes, infusion pumps, etc.) for administration to the patient. During this process, a peptide solution from the library may be diluted (e.g., around 5×, 10×, 100×, or other dilution) in a physiologically acceptable buffer for administration to a patient. An adjuvant also may be added at this stage. This procedure can be followed for a plurality of patients, for example at a hospital or other medical center.

Accordingly, in some embodiments a library can include a plurality (e.g., all, or a subset of) the peptides in Table A and a vaccine can be selected from that library based on the criteria described in this application. However, other libraries can be used (e.g., containing one or more of the peptides listed in Table A, and/or one or more other neoantigenic peptides) as described in this application.

TABLE A Peptides for vaccine library. SEQ ID NO. Long peptide for vaccine Exons Fusion name 1 AIKSKNVDVNVKDEETEVKSEEGPGWTILR E5:E5 ACBD6/RRP15 2 EAPLNPKANREKMTQDPLLGMLDGREDLER E3:E7 ACTB/GLI1 3 EAPLNPKANREKMTQPISGIPSPDESPKRA E3:E5 4 EAPLNPKANREKMTQLKSELDMLVGKCREE E3:E6 5 PRAVFPSIVGRPRHQLKSELDMLVGKCREE E2:E6 6 QTKVLSASQAFAAQRDSITQHKVCAPENYL E5:E14 AGPAT5/MCPH1 7 NDKLQKELNVLKSEQDLIRDQGFRGDGGST E8:E9 AKAP9/BRAF 8 QERERDPQQEQERERIDDVIDEIISLESSY E7:E5 ASPSCR1/TFE3 9 QERERDPQQEQERERLPVSGNLLDVYSSQG E7:E6 10 SSQKAHGILARRPSYRTHG E3:E10 ATF1/EWSR1 11 MSVPTPIYQTSSGQYSSFRQDHPSSMGVYG E4:E8 12 RNVQDFKRASEEITKTTQDGLDWLIST E10:E11 ATG4C/FBX038 13 TPAQLYTLQPKLPITVYRRKHQELQAMQME E7:E20 ATIC/ALK 14 TQLPHIPVAVRVGCLQYYRTDSDNQAILSE E9:E21 BBS9/PKD1L1 15 KTRVYRDTAEPNWNEKPFSGQ E15:E2 BCR/ABL1 16 RKQTGVFGVKIAVVTKSPSAASSI E18:E2 17 EITPRRQSMTVKKGESYTFLISSDYERAEW E8:E12 18 KLQTVHSIPLTINKEAGSIEALQRPVASDF E13:E2 19 KTRVYRDTAEPNWNELDPQALQDRDWQRTV E15:E17 20 QWSHQQRVGDLFQKLNLRARSNKDAKDPTT E4:E6 21 SRDALVSGALESTKATKAKPFSGQ E2:E2 22 SNKDAKDPTTKNSLEKALQRPVASDFEPQG E6:E2 23 ASEETYLSHLEALLLKPFSGQ E3:E2 24 EITPRRQSMTVKKGEKPFSGQ E8:E2 25 KLQTVHSIPLTINKEGEKLRVLGYNHNGEW E13:E3 26 GVATDIQALKAAFDVRPSPCEDRHWPGLAL E19:E1 27 GVATDIQALKAAFDVKALQRPVASDFEPQG E19:E2 28 QIWPNDGEGAFHGDAGEKLRVLGYNHNGEW E1:E3 29 LNVIVHSATGFKQSSSEKLRVLGYNHNGEW E14:E3 30 LNVIVHSATGFKQSSKALQRPVASDFEPQG E14:E2 31 KLQTVHSIPLTINKEEALQRPVASDFEPQG E13:E2 32 QIWPNDGEGAFHGDAEALQRPVASDFEPQG E1:E2 33 QIWPNDGEGAFHGDADYELLTENDMLPNMR E1:E19 BCR/JAK2 34 QIWPNDGEGAFHGDAVLQERIPWVPPECIE E1:E17 35 APNVHINTIEPVNIDNDLRLQMEAQRICLS E8:E9 BRAF/AKAP9 36 RYVKSCLQKKQRKPFSSALPGPDMSMKPSA E10:E2 BRD3/NUTM1 37 SSSESSSSDSEDSETASALPGPDMSMKPSA E11:E2 38 SEFREGVRKIAREQKVYRRKHQELQAMQME E17:E20 CARS/ALK 39 LQEENRDLRKASVTIEDPKWEFPRKNLVLG E1:E12 CCDC6/RET 40 EEEFLTNELSRKLMQEDPKWEFPRKNLVLG E2:E12 41 SRHSLEQKPTDAPPKVVVHRRLKNQKSAKEG E6:E35 CD74/ROS1 42 SRHSLEQKPTDAPPKAGVPNKPGIPKLLEG E6:E32 43 SRHSLEQKPTDAPPKDDFWIPETSFILTII E6:E34 44 VHPDALNRFGKTALQLHVHACLLTRKQEDC E2:E3 CDKN2D/WDFY2 45 VHPDALNRFGKTALQLHVHACLLTRKQEDC E2:E3 46 VHPDALNRFGKTALQLHVHACLLTRKQEDC E2:E3 47 LAENITQERDSLMCLDLIRDQGFRGDGGST E16:E9 CEP89/BRAF 48 TQEEEDEILPRKDYEKTLGRRDSSDDWEIP E2:E11 CLCN6/BRAF 49 EERSVLNNQLLEMKKSTLPTQEEIENLPAF E20:E36 CLIP1/ROS1 50 RKEEEQATETQPIVYVYRRKHQELQAMQME E31:E20 CLTC/ALK 51 AMPYFIQVMKEYLTKGVYRRKHQELQAMQM E30:E20 52 AMPYFIQVMKEYLTKCTAGSTRSCKPCRWS E30:E20 53 CVAYERGQCDLELINLPVSGNLLDVYSSQG E17:E6 CLTC/TFE3 54 GKAGERGVPGPPGAVGDPIPEELYEMLSDH E26:E2 COL1A1/PDGFB 55 GPSGPRGLPGPPGAPGDPIPEELYEMLSDH E7:E2 56 GAPGAKGARGSAGPPGDPIPEELYEMLSDH E37:E2 57 GPSGPAGPTGARGAPGDPIPEELYEMLSDH E34:E2 58 GPPGPAGPAGPPGPIGDPIPEELYEMLSDH E36:E2 59 GPPGPRGRTGDAGPVGDPIPEELYEMLSDH E47:E2 60 GPAGPPGFPGAVGAKGDPIPEELYEMLSDH E16:E2 61 GPRGANGAPGNDGAKGDPIPEELYEMLSDH E31:E2 62 GKPGRPGERGPPGPQGDPIPEELYEMLSDH E10:E2 63 YDEKSTGGISVPGPMGDPIPEELYEMLSDH E6:E2 64 GPQGPGGPPGPKGNSGDPIPEELYEMLSDH E19:E2 65 GLPGTAGLPGMKGHRGDPIPEELYEMLSDH E11:E2 66 GNPGADGQPGAKGANGDPIPEELYEMLSDH E18:E2 67 KRHVWFGESMTDGFQGDPIPEELYEMLSDH E49:E2 68 RTCRDLKMCHSDWKSGGPHSRGAL E48:E2 69 GFQGPPGEPGEPGASGDPIPEELYEMLSDH E8:E2 70 GEPGSPGENGAPGQMGDPIPEELYEMLSDH E13:E2 71 GHRGFSGLQGPPGPPGDPIPEELYEMLSDH E45:E2 72 GPIGPPGPAGAPGDKGDPIPEELYEMLSDH E33:E2 73 GQAGVMGFPGPKGAAGDPIPEELYEMLSDH E25:E2 74 PPGPPGPPGPPGLGGGDPIPEELYEMLSDH E5:E2 75 GKDGEAGAQGPPGPAGDPIPEELYEMLSDH E27:E2 76 GQRGERGFPGLPGPSGDPIPEELYEMLSDH E40:E2 77 GPPGLAGPPGESGREGDPIPEELYEMLSDH E41:E2 78 GPAGPVGPVGARGPAGDPIPEELYEMLSDH E44:E2 79 GVPGDLGAPGPSGARGDPIPEELYEMLSDH E30:E2 80 GLPGERGRPGAPGPAGDPIPEELYEMLSDH E14:E2 81 GPAGEKGSPGADGPAGDPIPEELYEMLSDH E39:E2 82 GARGNDGATGAAGPPGDPIPEELYEMLSDH E15:E2 83 GEPGPPGPAGAAGPAGDPIPEELYEMLSDH E17:E2 84 GAPGSKGDTGAKGEPGDPIPEELYEMLSDH E20:E2 85 GAEGSPGRDGSPGAKGDPIPEELYEMLSDH E42:E2 86 GEAGRPGEAGLPGAKGDPIPEELYEMLSDH E23:E2 87 GFPGAAGRVGPPGPSGDPIPEELYEMLSDH E38:E2 88 GPAGPPGEAGKPGEQGDPIPEELYEMLSDH E29:E2 89 GEQGPSGASGPAGPRGDPIPEELYEMLSDH E46:E2 90 GPVGPAGKSGDRGETGDPIPEELYEMLSDH E43:E2 91 GERGAAGLPGPKGDRGDPIPEELYEMLSDH E32:E2 92 THGQEEGQVEGQDEDRWTVV E1:E2 COL1A1/USP6 93 THGQEEGQVEGQDEDTKNTIK E1:E1 94 TLLLLAVTLCLATCQYVVPKWEGLDSTLFHE E1:E3 COL1A2/PLAG1 95 TLLLLAVTLCLATCQCCLLVLPWPYLAPRM E1:E2 96 APSALSSSPLLTAPHRK E5:E7 CREB3L2/FUS 97 APSALSSSPLLTAPHVTMAKINPP E5:E6 98 ELSEPGDGEALMYHTALGTKDHVMTPNRII E1:E8 99 ELSEPGDGEALMYHTALGTKDHVMTP E1:E8 100 TRAFEQLMTDLTLSRLQGSLKRKQVVNLSP E1:E2 CRTC3/MAML2 101 SPPWDQDRRMMFPPPGILTNVI E20:E10 CTAGE5/SIP1 102 PPPSGIATLVSGIAGVYRRKHQELQAMQME E26:E20 DCTN1/ALK 103 DCVLVLLLMPRLICKCTAGSTRSCKPCRWS E16:E20 104 RHLVFPLLEFLSVKELVMYQIPFARVVCLV E1:E3 EIF3E/RSPO2 105 RHLVFPLLEFLSVKEVRGGEMLIALN E1:E2 106 NKYIMSNSGDYEILYLYRRKHQELQAMQME E20:E20 EML4/ALK 107 ILRGTFNDGFQIEVQCTAGSTRSCKPCRWS E15:E20 108 HTDGNEQLSVMRYSIVYRRKHQELQAMQME E18:E20 109 VTKTADKHKDVIINQVSPTPEPHLPLSLIL E6:E19 110 SEDHVASVKKSVSSKVYRRKHQELQAMQME E2:E20 111 IILWDHDLNPEREIECTAGSTRSCKPCRWS E14:E20 112 WSKTTVEPTPGKGPKVYRRKHQELQAMQME E13:E20 113 VTKTADKHKDVIINQVYRRKHQELQAMQME E6:E20 114 STSTQSKSSSGSAHFGPPRMQWRSPPG E10:E2 EPC1/PHF1 115 ECEQAERLGAVDESLRKYIFKPRTV E5:E5 ERO1L/FERMT2 116 ALRMEEDSIRLPAHLPKNRGIAIPVDLDSQ E2:E35 ETV6/ITPR2 117 IHTQPEVILHQNHEEGRKHPYSWECMCQKY E4:E16 ETV6/JAK2 118 IHTQPEVILHQNHEEVLQERIPWVPPECIE E4:E17 119 VSPPEEHAMPIGRIADYELLTENDMLPNMR E5:E19 120 VSPPEEHAMPIGRIADKSNLLVFRTNGVSD E5:E12 121 VSPPEEHAMPIGRIADVQHIKRRDIVLKRE E5:E15 ETV6/NTRK3 122 IHTQPEVILHQNHEEGPVAVISGEEDSASP E4:E14 123 VSPPEEHAMPIGRIAGPVAVISGEEDSASP E5:E14 124 IHTQPEVILHQNHEEDVQHIKRRDIVLKRE E4:E15 125 APSQYSQQSSSYGQQIAIAPNGALQLASPG E7:E5 EWSR1/ATF1 126 APSQYSQQSSSYGQQKKLLENVAERRKNM E7:E7 127 GMGSAGERGGFNKPGEKF E9:E4 128 GGMSRGGRGGGRGGMGKILKDLSSEDTRGR E8:E4 129 APSQYSQQSSSYGQQIAITQGGAIQLANNG E7:E7 EWSR1/CREB1 130 NKPGGPMDEGPDLDLVFKKEVYLHTSPHLK E10:E2 EWSR1/DDIT3 131 LPPREGRGMPPPLRGVFKKEVYLHTSPHLK E13:E2 132 APSQYSQQSSSYGQQMFKKEVYLHTSPHLK E7:E2 133 APSQYSQQSSSYGQQTAQPSPSTVPKTEDQ E7:E9 EWSR1/ERG 134 APSQYSQQSSSYGQQNPYQILGPTSSRLAN E7:E10 135 NKPGGPMDEGPDLDLDLPYEPPRRSAWTGH E10:E8 136 APSQYSQQSSSYGQQSSGQIQLWQFLLELL E7:E11 137 APSQYSQQSSSYGQQNLPYEPPRRSAWTGH E7:E8 138 APSQYSQQSSSYGQQRDIKQEPGMYREGPT E7:E12 EWSR1/ETV1 139 NKPGGPMDEGPDLDLDPVGDGLFKDGKNPS E10:E2 EWSR1/FEV 140 APSQYSQQSSSYGQQNPVGDGLFKDGKNPS E7:E2 141 GGMSRGGRGGGRGGMGIPVTASLPPLEWPL E8:E3 EWSR1/NFATC2 142 YEDPPTAKAAVEWFDDMPCVQAQYSPSPPG E12:E3 EWSR1/NR4A3 143 APSQYSQQSSSYGQQRPMDEGPDLDLGPPV E7:E10 144 GMGSAGERGGFNKPGGPPVDPDEDSDNSAI E9:E11 145 LPPREGRGMPPPLRGDMPCVQAQYSPSPPG E13:E3 146 NKPGGPMDEGPDLDLDMPCVQAQYSPSPPG E10:E3 147 YEDPPTAKAAVEWFDEPTAEEGSPASPGPE E12:E2 148 APSQYSQQSSSYGQQKPTAEEGSPASPGPE E7:E2 149 APSQYSQQSSSYGQQSGRDGISTSKRQKS E7:E5 EWSR1/PBX1 150 GGMSRGGRGGGRGGMGRKRRNFNKQATEIL E8:E5 151 APSQYSQQSSSYGQQNVKWGKLRDYQVRGL E7:E5 EWSR1/SMARCA5 152 GGMSRGGRGGGRGGMGGTNLGKKKQHICHI E8:E6 EWSR1/SP3 153 YGQTAYATSYGQPPTEGTSTGYTTPTAPQA E4:E5 EWSR1/WT1 154 AYPAYGQQPAATAPTSSAGERGGFNKPG E5:E9 155 AYPAYGQQPAATAPTSYSSTQPTSYDQSSY E5:E7 156 APSQYSQQSSSYGQQNEKKDIDHETVVEEQ E7:E2 EWSR1/YY1 157 GGMSRGGRGGGRGGMGRHRPWG E8:E5 EWSR1/ZNF444 158 LRLQDYEEKTKKAERDDFWIPETSFILTII E10:E34 EZR/ROS1 159 TSSLHGSSLHRPSTEDLIRDQGFRGDGGST E2:E9 FAM131B/BRAF 160 MGCIGSRTVGSTTGLSATPPASLPG E1:E10 161 STEQTRTDFSWDGINDLIRDQGFRGDGGST E3:E9 162 MASSGERTPSNALDPRWRSLW E1:E17 FBXL18/RNF216 163 RLSEARLSQRDLSPTDLIRDQGFRGDGGST E13:E9 FCHSD1/BRAF 164 ATLCTARPSPTLPEQDWPKWEGLDSTLFHE E2:E3 FGFR1/PLAG1 165 ATLCTARPSPTLPEQGCLLVLPWPYLAPRM E2:E2 166 LVEDLDRIVALTSNQGLLESSAEKAPVSVS E17:E7 FGFR1/TACC1 167 ARDIHHIDYYKKTTNLDAKKSPLALLAQTC E14:E2 FGFR1/ZNF703 168 LVEDLDRVLTVTSTDNVMEQFNPGLRNLIN E17:E2 FGFR3/BAIAP2L1 169 LVEDLDRVLTVTSTDFKESALRKQSLYLKF E17:E8 FGFR3/TACC3 170 LVEDLDRVLTVTSTDVPGPPPGVPAPGGPP E17:E10 171 LVEDLDRVLTVTSTDVKATQEENRELRSRC E17:E11 172 RKAGDFHRNDSIYEEPQQVVQKKPAQEETE E8:E4 FHIT/HMGA2 173 YFKDKGDSNSSAGWKVMGLLTNHGGVPHQP E1:E8 FOXO1/PAX3 174 QYNSSSGGGGGGGGGVAIAPNGALQLASPG E5:E5 FUS/ATF1 175 EPRGRGGGRGGRGGMGPSGPPAFAAHPSEQ E6:E5 FUS/CREB3L2 176 EPRGRGGGRGGRGGMGNCRDQALWS E6:E6 177 EPRGRGGGRGGRGGMGPQWTTCICRPPLRA E6:E5 178 EPRGRGGGRGGRGGMGCLPSGPPAFAAHPS E6:E5 179 QYNSSSGGGGGGGGGAPVDHLHLPPTPPSS E5:E5 180 QYNSSSGGGGGGGGGETAGIRPSGPDRGGE E5:E6 181 GGMGGSDRGGFNKFGAPVDHLHLPPTPPSS E7:E5 182 QYNSSSGGGGGGGGGVFKKEVYLHTSPHLK E5:E2 FUS/DDIT3 183 EPRGRGGGRGGRGGMGVQEGSVSSYITTPE E6:E2 184 GGMGGSDRGGFNKFGVFKKEVYLHTSPHLK E7:E2 185 GYGQSSYSSYGQSQNMFKKEVYLHTSPHLK E3:E2 186 FNRGGGNGRGGRGRGVFKKEVYLHTSPHLK E11:E2 187 IESVADYFKQIGIIKTDPTAEMAAESLPFS E9:E3 188 NKFGGPRDQGSRHDSVFKKEVYLHTSPHLK E8:E2 189 EPRGRGGGRGGRGGMGGSDRGGFNKFG E6:E7 FUS/ERG 190 GGMGGSDRGGFNKFGDLPYEPPRRSAWTGH E7:E8 191 NKFGGPRDQGSRHDSAAQPSPSTVPKTEDQ E8:E9 192 QYNSSSGGGGGGGGGDLPYEPPRRSAWTGH E5:E8 193 GGMGGSDRGGFNKFGDPYQILGPTSSRLAN E7:E10 194 GGMGGSDRGGFNKFGGSGQIQLWQFLLELL E7:E11 195 EPRGRGGGRGGRGGMGQWPDPALAVPPGAP E6:E11 196 FDDPPSAKAAIDWFDDPVGDGLFKDGKNPS E10:E2 FUS/FEV 197 RAENACVPPFTIEVKKTLGRRDSSDDWEIP E2:E11 GATM/BRAF 198 PLEGDMSSPNSTGIQIMFETFNTPAMYVAI E6:E4 GLI1/ACTB 199 MIPHPQSRGPFPTCQIMFETFNTPAMYVAI E5:E4 200 GKPRNVALITGITGQPLHICQP E1:E22 GMDS/PDE8B 201 EDGEKAAREVKLLLLGSTTGLSATPPASLP E1:E10 GNAI1/BRAF 202 QKLMGQIHQLRSELQEDPKWEFPRKNLVLG E7:E12 GOLGA5/RET 203 GARLAAKYLDKELAGSTLPTQEEIENLPAF E4:E36 GOPC/ROS1 204 GASCKDTSGEIKVLQVWHRRLKNQKSAKEG E8:E35 205 LINIMIEPQATRKAQDAIRSHSESASPSAL E16:E8 HACLI/RAFI 206 EVLRNLSSPGWENISSLLFVSKFFEHHPIP E4:E7 HERPUDI/BRAF 207 MTVDHLKMLHTAGGKAFNNPRPGQLGRLLP E4:E13 HEY1/NCOA2 208 VVASTISGKSQIEETVYRRKHQELQAMQME E28:E20 HIP1/ALK 209 KKHYELAGVAEGWEEVYRRKHQELQAMQME E30:E20 210 HGATTCLRAPPEPADLYRRKHQELQAMQME E21:E20 211 SDSAQGSDVSLTACKDDFWIPETSFILTII E9:E34 HLA-A/ROS1 212 EATGEKRPRGRPRKWVTVKVPQKNS E3:E13 HMGA2/ALDH2 213 PKGSKNKSPSKAAQKVHQERLYQEYNFSKA E2:E6 HMGA2/CCNB1IP1 214 EATGEKRPRGRPRKWNFFRLNYLEVCH E3:E4 HMGA2/COX6C 215 EATGEKRPRGRPRKWVVVSTTVNVDGHVLA E3:E8 HMGA2/EBF1 216 EATGEKRPRGRPRKWLQKHDKEDFPASWRS E3:E9 HMGA2/FHIT 217 EATGEKRPRGRPRKWGSVKSAGPTTAREQV E3:E4 HMGA2/LHFP 218 PRKWPQQVVQKKPAQSWYLG E4:E12 HMGA2/NFIB 219 EATGEKRPRGRPRKWSWYLG E3:E12 220 EATGEKRPRGRPRKWVILTNQITTHLSGAL E3:E8 HMGA2/RAD51B 221 EATGEKRPRGRPRKWLSASLAVVHMEPAMN E3:E9 HMGA2/WIF1 222 EATGEKRPRGRPRKWGTKPASYMP E3:E10 223 EATGEKRPRGRPRKWAEYFYEFLSLRSLDK E3:E3 224 EATGEKRPRGRPRKWLFKLVSHVLENRMGW E3:E4 225 PRKWPQQVVQKKPAQGTKPASYMP E4:E10 226 MESQRGRNCNEKPTNVR E1:E4 HNRNPA2B1/ETV1 227 KANAARSQLETYKRQEDPKWEFPRKNLVLG E11:E12 HOOK3/RET 228 SRSPPAENEVSTPMQKKKGGRGLMTENTMR E7:E3 IL6R/ATP8B2 229 SVEGVVRILLEHYYKAWKKRWFILRSGRMS E2:E2 INTS4/GAB2 230 SFRAIIRDLNSLFTPDCRLLWDYVYQLLSD E18:E6 JAK2/ETV6 231 NIIFQFTKCCPPKPKETGSDFSMFEALRDT E11:E25 JAK2/PCM1 232 SPKDFNKYFLTFAVEEAESGNISQKSDEED E10:E37 233 PPITPSSSFRSSTPTGPPRMQWRSPPG E3:E2 JAZF1/PHF1 234 PPITPSSSFRSSTPTEPTQIYRFLRTRNLI E3:E2 JAZF1/SUZ12 235 DLAEIGIAVGNNDVKEDPKWEFPRKNLVLG E15:E12 KIF5B/RET 236 VRSKNMARRGHSAQIDPLCDELCRTVIAAA E24:E11 237 LRKLFVQDLATRVKKEDPKWEFPRKNLVLG E22:E12 238 FLENNLEQLTKVHKQEDPKWEFPRKNLVLG E23:E12 239 VRSKNMARRGHSAQIDVAEEAGCPLSCAVS E24:E8 240 ENEKELAACQLRISQEDPKWEFPRKNLVLG E16:E12 241 EILTRAHEREFGSVDVYRRKHQELQAMQME E9:E20 KLC1/ALK 242 TLEGELHDLRGQVAKTLTAHLETRWRRRTK E2:E10 LMNA/NTRK1 243 TSSGAGFFLPQHDSSVWHRRLKNQKSAKEG E16:E35 LRIG3/ROS1 244 RGGRGGREFADFEYRDLIRDQGFRGDGGST E9:E9 LSM14A/BRAF 245 RKDEELTSSQRDLAVRDLKLDNILLDAEGH E6:E12 MBOAT2/PRKCE 246 QKKKAKSQQYKGHKKRTGWAPPTFLLYQFA E16:E1 MBTD1/CXorf67 247 SHHSSHKKRKNKNRHRPPQDAMAQPPRLSR E5:E2 MEAF6/PHF1 248 VLHPMDAAQRSQHIKKTLGRRDSSDDWEIP E4:E11 MKRN1/BRAF 249 KNLLEFAETLQFIDSFLNTSSNHENSDLEM E9:E11 MYB/NFIB 250 AFTVPKNRSLASPLQSWYLG E15:E12 251 AFTVPKNRSLASPLQPNGSGQVVGKVPGHF E15:E9 252 AFTVPKNRSLASPLQSSQLELHLHLHRCHF E15:E8 253 LMSTENELKGQQVLPLRICDWTMNQNGRHL E8:E11 254 AFTVPKNRSLASPLQPTQPQAHLKPIDMWD E15:E10 255 AFTVPKNRSLASPLQLRICDWTMNQNGRHL E15:E11 256 LMSTENELKGQQVLPPNGSGQVVGKVPGHF E8:E9 257 FQENGPPLLKKIKQESWYLG E13:E12 258 FQENGPPLLKKIKQELRICDWTMNQNGRHL E13:E11 259 LMSTENELKGQQVLPSWYLG E8:E12 260 EALNHRIVQQAKEMTVWHRRLKNQKSAKEG E23:E35 MYO5A/ROS1 261 FDSKRREGKQLSLHEATSKSQIMSLWGLVS E2:E2 NAB2/STAT6 262 DSASLSGESLDGHLQAEQMGKDGRGYVPAT E5:E17 263 QVARESTYLSSLKGSRQPPSPRSCLCGVWS E3:E2 264 QVARESTYLSSLKGSRPQVYPPHSHSIPPY E3:E19 265 DSASLSGESLDGHLQGTNHFLPQSSRCLPW E5:E18 266 PEELGGPPLKKLKQEGPTTSYPRAPDAYHG E4:E18 267 FDSKRREGKQLSLHECLCTA E2:E6 268 QVARESTYLSSLKGSRDQPLPTPELQMPTM E3:E18 269 PEELGGPPLKKLKQEGVPGRLRRLLLQLG E4:E3 270 QVARESTYLSSLKGSRPHLQMPPSLGQMSL E3:E20 271 DSASLSGESLDGHLQGSPQIENIQPFSAKD E5:E16 272 QVARESTYLSSLKGSS E3:E17 273 PEELGGPPLKKLKQEATSKSQIMSLWGLVS E4:E2 274 PEELGGPPLKKLKQESIYQRDPLKLVATFR E4:E4 275 FDSKRREGKQLSLHEFRHLPMPFHWKQEEL E2:E5 276 VGRLSPCVPAKPPLAAEQMGKDGRGYVPAT E6:E17 277 VGRLSPCVPAKPPLAGNLQVPDHVSVGSGL E6:E2 278 VGRLSPCVPAKPPLAGSPQIENIQPFSAKD E6:E16 279 PEELGGPPLKKLKQEFLFSVSSELQGGTWV E4:E1 280 VGRLSPCVPAKPPLAGTNHFLPQSSRCLPW E6:E18 281 PSRKPLDSRVLNAVKYYGTAANDIGDTTNR E4:E13 NACC2/NTRK2 282 KGETITGLLQEFDVQEALSVVSEDQSLFEC E3:E4 NDRG1/ERG 283 DVDLAEVKPLVEKGEEALSVVSEDQSLFEC E2:E4 284 PIAMALANVVPCSQWVFTKYGKCYMFNSGE E27:E2 NF1/ACCN1 285 PPTWPKPLVPAIPICSSAGERGGFNKPGGP E2:E9 NFATC2/EWSR1 286 MRRQQEGFKGTFPDALPVSGNLLDVYSSQG E9:E6 NONO/TFE3 287 GEVDADCMDVNVRGPAGPSRTGYLHPPSPG E30:E14 NOTCH1/GABBR2 288 KCGSGPVHISGQHLVVYRRKHQELQAMQME E5:E20 NPM1/ALK 289 VAPPTTAASSVEEPEGHRESNSRLPGPPEG E5:E11 NTN1/ACLY 290 FMDNPFEFNPEDPIPDKLKCTKEEHLCTQR E9:E8 NTRK1/TPM3 291 PQYFRQGHNCHKPDTYCRLLWDYVYQLLSD E14:E6 NTRK3/ETV6 292 MDRDLSYNLLEDLPSFSV E1:E12 NUP107/LGR5 293 SNPMNPTIGNGLSPQNSIRHNLSLHSKFIR E7:E2 PAX3/FOXO1 294 SNPMNPTIGNGLSPQFTADLDQFDQLLPTL E7:E14 PAX3/NCOA1 295 YQLSETSYQPTSIPQGLPELELEAIDNQFG E6:E15 296 SNPMNPTIGNGLSPQPGSELDNLEEILDDL E7:E12 PAX3/NCOA2 297 PSNHMNPVSNGLSPQNSIRHNLSLHSKFIR E7:E2 PAX7/FOXO1 298 LGRNLSTHQTYPVVAGREMVGPTLPGYPPH E8:E10 PAX8/PPARG 299 AGSPDTESPVLVNDYRENVIEYKHCLITKN E36:E11 PCM1/JAK2 300 AGSPDTESPVLVNDYEIELSSLREALSFVS E36:E9 301 LEKIIKCNRSTEISSVLQERIPWVPPECIE E24:E17 302 KKRNSTQLKSRVKNINKSNLLVFRTNGVSD E23:E12 303 NSELTPSESLATTDDEIELSSLREALSFVS E26:E9 304 RQIKAIMKEVIPFLKEDPKWEFPRKNLVLG E29:E12 PCM1/RET 305 GVACEPLPDRYTVSEESNGWK E13:E4 PLXND1/TMCC1 306 LQPMAGTCPAPEIHAIERLEVSSLAQTSSA E12:E4 307 DSERLQYEKKLKSTKCTAGSTRSCKPCRWS E8:E20 PPFIBP1/ALK 308 YKKMQDTVVLAQGKKVYRRKHQELQAMQME E12:E20 PPFIBP1/ALK 309 LVCKMKGEGVEIVDRVWHRRLKNQKSAKEG E9:E35 PPFIBP1/ROS1 310 KEPVKIAAPELHKGDVQTHLENPTRYHLQQ E1:E4 PRCC/TFE3 311 PQEIAPDASFIDDEAVQTHLENPTRYHLQQ E4:E4 312 DSEEDEPTKKKTILQLPVSGNLLDVYSSQG E2:E6 313 KEPVKIAAPELHKGDIDDVIDEIISLESSY E1:E5 314 KLWGIDRDSYRRILMEDPKWEFPRKNLVLG E7:E12 PRKAR1A/RET 315 SPWPLLGSAQGQFSAVHPNVSQGCQGGCAT E1:E2 PTPRK/RSPO3 316 TGLPGPPLITRTKCAVHPNVSQGCQGGCAT E7:E2 317 FGEKLFSGVLMDLSKSTLPTQEEIENLPAF E1:E36 PWWP2A/ROS1 318 ATSILEYPIEPSGVLGPASVISNDDDSASP E6:E16 QKI/NTRK2 319 EASSLKYLAEEFSIPEPTGEPSPKRPRGRP E7:E2 RAD51B/HMGA2 320 EASSLKYLAEEFSIPKAEATGEKRPRGRPR E7:E3 RAD51B/HMGA2 321 HMVSTTLPVDSRMIESTANPETPNSTISRE E7:E2 RAF1/DAZL 322 DGYQGSQTFHGAPLTVYRRKHQELQAMQME E18:E20 RANBP2/ALK 323 ASYDDPYKKAVAMSKR E2:E5 RBM14/PACS1 324 DSMENQVSVDAFKILDMEAQQVNEAESARE E11:E8 RET/GOLGA5 325 DSMENQVSVDAFKILKCERLLLYLYCHELS E11:E17 RET/TRIM33 326 EHRKELGPYVFREAQVNKLELELESAKQKF E22:E24 RGS22/SYCP1 327 FIQKIRYTNARDRNQDLIRDQGFRGDGGST E3:E9 RNF130/BRAF 328 TVQGSNIFERTEVLADDFWIPETSFILTII E4:E34 SDC4/ROS1 329 TVQGSNIFERTEVLAAGVPNKPGIPKLLEG E4:E32 330 GQESDDFELSGSGDLDDFWIPETSFILTII E2:E34 331 GQESDDFELSGSGDLVWHRRLKNQKSAKEG E2:E35 332 GQESDDFELSGSGDLAGVPNKPGIPKLLEG E2:E32 333 PGHMHTQVPPYPQPQLYRRKHQELQAMQME E19:E20 SEC31A/ALK 334 GTLPAASELPASQRTVYRRKHQELQAMQME E20:E20 335 GTLPAASELPASQRTVLQERIPWVPPECIE E20:E17 SEC31A/JAK2 336 MAATDLERFSNSYNNSQAPSPGLGS E1:E19 SEPT8/AFF4 337 VPPATMSGSMMGSDMLPVSGNLLDVYSSQG E9:E6 SFPQ/TFE3 338 VPPATMSGSMMGSDMIDDVIDEIISLESSY E9:E5 339 RQREESYSRMGYMDPIDDVIDEIISLESSY E7:E5 340 LEDMRSNNVEDCKMMVIHPKTDEQRCRLQE E17:E4 SLC26A6/PRKAR2A 341 VCSLDILSSAFQLVGDDFWIPETSFILTII E4:E34 SLC34A2/ROS1 342 VCSLDILSSAFQLVGAGVPNKPGIPKLLEG E4:E32 343 ILPYTLASLYHREKQLIAMDSAITLWQFLL E4: E2 SLC45A3/ELK4 344 LSSIRPPRLEGENTQDLIRDQGFRGDGGST E10:E9 SND1/BRAF 345 LSSIRPPRLEGENTQKTLGRRDSSDDWEIP E10:E11 346 PTANLDQKDKQFVAKDLIRDQGFRGDGGST E9:E9 347 SKKEVPIHRVADISGKTLGRRDSSDDWEIP E14:E11 348 SKKEVPIHRVADISGDLIRDQGFRGDGGST E14:E9 349 YSHKLFNGSMEAFIKRPRGQRDSSYYWEIE E12:E10 SRGAP3/RAF1 350 KQTLGEGERAECGTTRMQFEVTANQPHLQP E11:E8 351 GPPQPPQQRPYGYDQEWVSKSPSHLSCVIN E10:E4 SS18/SSX1 352 GPPQPPQQRPYGYDQLNILR E10:E5 353 QYPGQQGYPGQQQGYVEHPQMTFGRLHRII E9:E5 354 QYPGQQGYPGQQQGYGFKVTLPPFMCNKQA E9:E4 355 GPPQPPQQRPYGYDQIMPKKPAEDENDSKG E10:E6 356 TAPSAQQQRPYGYEQIMPKKPAEDENDSKG E10:E6 SS18L1/SSX1 357 GDGMPVGPVPPGFFQRENVIEYKHCLITKN E5:E11 SSBP2/JAK2 358 ETCEHSSEAKAFHDYRENVIEYKHCLITKN E4:E11 359 NITLGEPPGFLHSWWCEKMSLNINTV E3:E11 360 HPQMTFGRLHRIIPKGQYGNYQQ E5:E11 SSX1/SS18 361 YPKKPKDEAFRSHYKQFEEGLLDRCPAPGP E16:E7 STAT6/NAB2 362 TELNQGDMKPPSYDSVYRRKHQELQAMQME E3:E20 STRN/ALK 363 CTEKGTWRESTLTCTVLLQIL E6:E2 SUSD1/ROD1 364 RFAKKMDKMVQKKNAIGQNGKDWIPLSSTK E1:E3 TCEA1/PLAG1 365 HEGLSPTPFMNSNLMDMPCVQAQYSPSPPG E5:E3 TCF12/NR4A3 366 GYKILIPKGSYGRVKVS E7:E8 TECTA/TBCEL 367 SYLPGGTTGLQLPSTPVDREPVDREPVVCH E5:E8 TFE3/ASPSCR1 368 SPMALLTIGSSSEKEPVDREPVDREPVVCH E4:E8 369 QPPYTGAQTQAGQIEVYRRKHQELQAMQME E6:E20 TFG/ALK 370 KNVMSAFGLTDDQVSVYRRKHQELQAMQME E5:E20 371 EPPGEPGPSTNIPENVYRRKHQELQAMQME E4:E20 372 QAPPQQPQQYGIQYSDMPCVQAQYSPSPPG E7:E3 TFG/NR4A3 373 KNVMSAFGLTDDQVSDTNSTSGDPVEKKDE E5:E10 TFG/NTRK1 374 MALNSEALSVVSEDQSLFEC E2:E4 TMPRSS2/ERG 375 MALNSPSGSEQLVDGLAY E2:E3 376 FLVGAALAAGLLWKFRTLLMNAVWPKAGRW E4:E5 277 FLVGAALAAGLLWKFRSLISCE E4:E4 378 DGVSHCPGGEDENRCGSLISCE E5:E4 379 MALNSVIPGSLETRGKPC E2:E2 380 VCTQPKSPSGTVCTSRSLISCE E3:E4 381 VCTQPKSPSGTVCTSSYSRIFGDPRKAVLT E3:E2 382 MALNSLRYLTMMSSLYQTIR E2:E6 TMPRSS2/ETV1 383 VCTQPKSPSGTVCTSRGSLFPQKLLNAETS E3:E2 384 KGEPHHELPPGSTKRVPASVQLHTAVEMHH E8:E9 TP53/NTRK1 385 DAQAGKEPGGSRAHSSPGQCAAAHGGGDAP E10:E9 386 QPKKKPLDGEYFTLQSRPVCSCTRRWRCTT E9:E9 387 ERSVAKLEKTIDDLEVYRRKHQELQAMQME E7:E20 TPM3/ALK 388 ERSVAKLEKTIDDLEDTNSTSGDPVEKKDE E7:E10 TPM3/NTRK1 389 ERSVAKLEKTIDDLEVWHRRLKNQKSAKEG E8:E35 TPM3/ROS1 390 LQKLEEAEKAADESESTLPTQEEIENLPAF E2:E36 391 PRMQGPIQQPSISHQEDPKWEFPRKNLVLG E9:E12 TRIM24/RET 392 QLEEKQQQPTRELLQEDPKWEFPRKNLVLG E3:E12 393 KKGKTAQGLSPVDQREDPKWEFPRKNLVLG E16:E12 394 VISAENWKPATKTDQGLLKMTEYKLVVVGA E3:E2 UBE2L3/KRAS 395 RNELLGDDGNSSENQSNKVPVVQHPHHVHP E4:E5 VTI1A/TCF7L2 396 MRSYKQEMGKLETDFSNKVPVVQHPHHVHP E3:E5 397 MRSYKQEMGKLETDFYLQMKWPLLDVQAGS E3:E4 398 MVANVEKQLEEAKELSNKVPVVQHPHHVHP E2:E5 399 LRDNLTLWTSDMQGDAYPALGPGVTANPGT E5:E2 YWHAE/FAM22A 400 LRDNLTLWTSDMQGDAYPVLGPGVTANPGT E5:E2 YWHAE/NUTM2B 401 IKTLEGEFSVTMWSSGPMDEGPDLDLGPPV E1:E10 YY1/EWSR1 402 FGSTRGSLDKPDSFMGEYSVGNKHRDPFEA E10:E7 ZC3H7B/BCOR 403 QCKTETQESQAFQERGSTTGLSATPPASLP E3:E10 ZSCAN30/BRAF

In some embodiments, the fusion-specific vaccine library comprises 2 or more (e.g., 2-5, 5-10, 10-25, 25-50, 50-100, 100-500, 500-1,000 or more) different fusion junction sequences that can be used as therapeutic vaccines for treating cancer.

In some embodiments, a method was developed for constructing a fusion-specific vaccine library from publicly available data such as but not limited to whole genome sequencing (WGS) data and/or RNA-sequencing data. In some embodiments, sources of publicly available data are databases such as but not limited to COSMIC (cancer.sanger.ac.uk/cosmic/), TCGA Fusion Gene Data Portal (54.84.12.177/PanCanFusV2/), and/or FusionCancer Database (donglab.ecnu.edu.cn/databases/FusionCancer/).

In some embodiments, neoantigenic peptides having amino acid sequences corresponding to the gene fusion junction can be generated. In some embodiments, a library of recurrent fusion-derived neoantigenic peptide vaccines can be constructed containing all cancer-associated neoantigenic peptides or subsets thereof. In some embodiments, a library can contain 2 or more different fusion peptides (e.g., 2-5, 5-10, 10-25, 25-50, 50-100, 100-500, 500-1,000 or more different fusion peptides).

In some embodiments, methods are disclosed for construction of a fusion-derived neoantigenic vaccine library, selection of patients and/or peptides for vaccination, and subsequent treating of patients with neoantigenic vaccines.

In some embodiments, methods for identifying recurrent fusion derived neoepitopes and constructing a vaccine library include several steps (FIG. 2). In some embodiments, methods comprise screening publicly available databases containing information regarding tumor whole genome sequencing (WGS) and/or RNA-sequencing data. In some embodiments, fusion genes and fusion transcripts can be de novo discovered using WGS and/or RNA-sequencing data. In some embodiments, methods integrate publicly available fusion-detection algorithms followed by heuristic filtering.

In some embodiments, methods comprise screening one or more publicly available databases containing information relating to annotated fusion genes, fusion transcripts, breakpoint coordinates of tumor-specific fusion genes, fusion proteins, and/or any resources containing information about recurrent fusions and their presence in tumor(s). In some embodiments, methods comprise screening peer-review articles. In some embodiments, methods comprise screening proprietary databases and/or patient sequence information.

In some embodiments, methods comprise further validation of fusion genes detected by screening publicly available databases containing WGS and/or RNA-sequencing data.

In some embodiments, methods comprise extracting fusion incidence data in cancer(s) from public data sources (e.g., cancer.org and/or cancer.net), proprietary information resources (e.g., uptodate.com) and/or peer-reviewed literature.

In some embodiments, methods comprise translating recurrent fusions to chimeric proteins, identifying long peptides at fusion breakpoints, and predicting peptide binding affinity to MHC class I proteins and/or MHC class II proteins using bioinformatics algorithms. In some embodiments, methods comprise determining peptide binding affinity to MHC proteins using biochemical techniques in vitro.

In some embodiments, methods comprise generating a set of T-cell epitopes by selection of fusion-derived neoepitopes having an IC₅₀ less than 500 nM. In some embodiments, the epitopes can bind HLA proteins and be recognized by T-cells. In some embodiments, IC₅₀ thresholds for MHC class I-peptide interaction are used for selecting peptides. In some embodiments, MHC class II-peptide interaction are used for selecting peptides.

In some embodiments, methods comprise determining a binding affinity of peptide-HLA class I major genes comprising HLA-A, HLA-B, and/or HLA-C. In some embodiments, methods comprise determining a binding affinity of peptide-HLA class I minor genes comprising HLA-E, HLA-F, and/or HLA-G. In some embodiments, methods comprise determining a binding affinity of peptide-HLA class II genes comprising HLA-DMA, HLA-DMB, HLA-DOA, HLA-DOB, HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DQB2, and/or HLA-DR. In some embodiments, methods comprise determining a binding affinity of the peptide to any antigen presenting protein.

In some embodiments, population coverage for each long peptide is calculated based on HLA allele frequency, wherein the HLA protein can bind to the fusion-derived neoepitopes with IC₅₀<500 nM. In some embodiments, patient coverage is calculated based on HLA allele frequency and gene fusion incidence rates in tumors. In some embodiments, the patient coverage is the percentage of patients having a particular tumor or tumors comprising a fusion-derived neoantigen included in the library. In some embodiments, patients having a particular tumor or tumors comprising a fusion-derived neoantigen included in the library are vaccinated with one or more fusion-specific vaccines from the library.

In some embodiments, fusion-specific vaccines from the library comprise fusion-derived long peptides having 25-30 amino acids. In some embodiments, fusion-specific vaccines from the library comprise fusion-derived long peptides having 30-50 amino acids. In some embodiments, fusion-specific vaccines from the library comprise fusion-derived long peptides having 50-100 amino acids. In some embodiments, fusion-specific vaccines from the library comprise fusion-derived long peptides encompassing the entire fusion protein.

In some embodiments, fusion-derived neoantigens can be modified by anchor residues, with additional amino acid sequences like T-helper epitopes that can be included in polypeptide for enhancing of in vivo processing, binding to MHC, and/or immunogenicity.

In some embodiments, fusion-derived long peptides in the library are characterized by their association with particular fusion genes from which peptides are derived. In some embodiments, fusion-derived long peptides in the library are characterized by listing the HLA proteins that can effectively present neoepitopes derived from the fusion-derived long peptide. In some embodiments, fusion-derived long peptides in the library are characterized by the population coverage of the fusion-derived long peptide.

In some embodiments, a vaccine library contains fusion-derived long peptides or polypeptides constructed of fusion-derived neoepitopes at the fusion breakpoint. In some embodiments, fusion-derived long peptides or polypeptides in the library are described by cancer types. In some embodiments, fusion-derived long peptides or polypeptides in the library are described by short peptides derived from long peptides, wherein the short peptides interact with MHC class I and/or MHC class II proteins. In some embodiments, fusion-derived long peptides or polypeptides in the library are described by the population coverage.

In some embodiments, the interactions between short peptides and MHC proteins are characterized by an IC₅₀, wherein the short peptides bind to MHC proteins with an IC₅₀<500 nM. In some embodiments, fusion-derived peptides are formulated with an appropriate carrier or adjuvant. In some embodiments, fusion-derived neoantigens are DNA and/or RNA. In some embodiments, a single vaccine can contain one or more long peptides. In some embodiments, a fusion-derived long peptide can produce several shorter peptides that bind to MHC proteins. In some embodiments, a vaccine targets one or more neoantigens. In some embodiments, a vaccine library targets more neoantigens than the number of vaccines in the library.

Peptide Length

In some embodiments, a fusion-derived peptide in a vaccine has a length of 7-11 amino acids. In some embodiments, the peptide has a length of 7 amino acids. In some embodiments, the peptide has a length of 8 amino acids. In some embodiments, the peptide has a length of 9 amino acids. In some embodiments, the peptide has a length of 10 amino acids. In some embodiments, the peptide has a length of 11 amino acids. In some embodiments the peptide length is 25 or more amino acids, 50 or more amino acids, 75 or more amino acids, or 100 or more amino acids. In some embodiments, the peptides are processed to a shorter length intracellularly. In some embodiments the neoantigenic fusion-derived peptides in the library can include, but are not limited to, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 60, 70, 80, 90, 100 or more amino acids. In some embodiments, long peptides in the library correspond to shorter peptides that bind to MHC proteins. In some embodiments, a peptide in a vaccine can be of any suitable length that is sufficient to be immunogenic in a patient.

Peptide Synthesis and Modification

In some embodiments, fusion-derived peptides are in neutral (uncharged) forms or in forms that are salts. Methods for synthesizing peptides are well known in the art. In one embodiment, the peptides provided herein are synthesized using an appropriate solid-state synthetic procedure (see for example, Steward and Young, Solid Phase Peptide Synthesis, Freemantle, San Francisco, Calif. (1968); Merrifield (1967) Recent Progress in Hormone Res 23: 451). However, any other suitable synthetic technique may be used. In some embodiments, one or more peptides provided herein are synthesized by expressing the peptides through standard molecular biological techniques. In some embodiments, one or more peptides provided herein are isolated from natural sources.

In some embodiments, fusion-derived peptides are modified. Modifications should not reduce biological activity of peptides and their ability to induce tumor-specific immune responses. Modifications include but are not limited to phosphorylation, glycosylation, and oxidation. In some embodiments, peptides described herein are linked to one or more additional moieties (e.g., that help promote or stimulate an immune response, stabilize or solubilize the peptide, etc., or any combination thereof).

In some embodiments, fusion-derived peptides are modified for enhancing their in vivo processing, binding to MHC, and/or immunogenicity. In some embodiments, fusion-derived peptide modifications include modification to anchor residues. In some embodiments, anchor residues are position 2 and position 8 in peptides comprising 9-10 amino acid residues. In some embodiments, peptide modifications comprise adding amino acid sequences like T-helper epitopes upstream or downstream.

In some embodiments, fusion-derived neoantigens comprise polypeptides consisting of repeating fusion-derived neoantigenic short peptides.

Patient Selection

In some embodiments, a patient is eligible for treatment with one or more fusion-specific vaccines from the library when the patient's tumor biopsy comprises one or more gene fusions corresponding to fusion-derived peptides or fusion-derived neoantigens present in the library.

In some embodiments, a patient is eligible for treatment with fusion-specific vaccines from the library when the long peptide in the library can bind to the HLA alleles of the patient and be presented to the patient's immune system. In some embodiments, long peptides in the library are characterized by the HLA alleles which can bind the long peptide derivatives and present them to the immune system.

In some embodiments, the long peptide or polypeptide at the point of junction must be able to produce neoantigens for a particular patient. In some embodiments, the patient is eligible for vaccination if at least one HLA allele of the patient matches the HLA allele of the particular fusion-derived neoantigen. In some embodiments, up to six HLA alleles of the patient match the HLA alleles of the particular fusion-derived neoantigen.

In some embodiments, a method of selecting a patient for vaccination with a therapeutic fusion-specific vaccine from a fusion-specific vaccine library is based on one or more factors (e.g., as illustrated in FIG. 3). In some embodiments, selecting a patient for vaccination with a therapeutic peptide vaccine from a fusion-specific vaccine library is based on genetic analysis of a patient's tumor sample (e.g., biopsy) and normal tissue sample. In some embodiments, genetic analysis is performed using one or more techniques that detects fusion genes, fusion transcripts, and/or fusion proteins in a patient's tumor. In some embodiments, genetic analysis is performed with whole genome sequencing, RNA sequencing, proteome sequencing, fluorescence in situ hybridization, pyrosequencing, qPCR, Sanger sequencing, or any known analysis method that allows identification of fusion genes or/and transcripts presented in a tumor sample and absent in a normal tissue sample.

In some embodiments, one or more gene fusions found with WGS and/or RNA sequencing are validated with in vitro techniques. In some embodiments, fusions identified by screening public and proprietary databases for information about the presence of a particular fusion in a particular cancer type are validated with in vitro techniques.

In some embodiments, selecting a patient for vaccination with a therapeutic peptide vaccine from a fusion-specific vaccine library is based on measuring the expression level of the fusion gene or transcript. In some embodiments, the expression level of the fusion gene or transcript is measured by RNA sequencing and/or any technique that measures the expression level of the fusion transcript(s) and/or the corresponding chimeric protein(s). In some embodiments, the fusion is expressed.

In some embodiments, selecting a patient for vaccination with a therapeutic fusion-specific vaccine from a fusion-specific vaccine library is based on the patient's HLA genotype. In some embodiments, the patient is HLA genotyped using one or more serological tests, PCR, WGS, WES, RNA sequencing, and/or any other technique that determines the patient's HLA genes and/or HLA proteins. In some embodiments, the patient's HLA genotyping can be performed in silico with patient's tumor sequencing data comprising transcriptome, exome, and/or genome sequencing data. In some embodiments, HLA genotyping should have at least a 4-digit resolution for matching a patient's HLA alleles to vaccines in the library. However, other thresholds can be used for HLA matching.

In some embodiments, selecting a patient for vaccination with a therapeutic fusion-specific vaccine from fusion-specific vaccine library is based on matching of patient's HLA alleles with HLA alleles that bind to fusion-derived long peptides in the vaccine library. In some embodiments, HLA proteins can bind to peptides derived from the fusion gene detected in a patient's tumor and bind to short peptides derived from long peptides presented in the library. In some embodiments, the patient is eligible for vaccination if at least one HLA allele of the patient matches the HLA allele of the particular fusion-derived peptide. In some embodiments, up to six HLA alleles of the patient matches the HLA alleles of the particular fusion-derived peptide.

In some embodiments, a patient is selected for vaccination with a therapeutic fusion-specific vaccine from the fusion-specific vaccine library if one or more of the fusion-derived long peptide(s) in library are found in the patient's tumor biopsy as part of the expressed fusion protein (e.g., a fusion gene or fusion transcript) and not found in normal tissue(s). In some embodiments, a patient is selected for vaccination with a therapeutic fusion-specific vaccine from the fusion-specific vaccine library if the patient has one or more HLA proteins that can effectively bind and present to the immune system one or more fusion-derived neoantigens that are present in the library. In some embodiments, at least one HLA allele of the patient must match one of the HLA alleles that bind to the fusion-derived neoantigens in the vaccine library.

In some embodiments, long peptides in a library might not bind to a patient's HLA proteins, whereas shorter peptides may bind to one or more of the patient's HLA proteins, and the patient is eligible for vaccination. For example, 30-mer peptides (peptides that are 30 amino acids long) cannot bind to MHC class I proteins, but derivatives of the 30-mer peptides, such as 8-mer, 9-mer, 10-mer, and/or 11-mer peptides will bind to the patient's HLA proteins and can be used to vaccinate the patient.

In some embodiments, a patient may have multiple HLA proteins that match multiple tumor-specific recurrent fusion-derived long peptides present in the library.

In some embodiments, protein mass spectrometry can be used for identifying fusion-derived peptides bound to a patient's HLA proteins. In some embodiments, peptides are eluted from HLA molecules on cancer cells and then analyzed with mass spectrometry and matched with peptides in the vaccine library.

In some embodiments, no appropriate vaccine in the library matches a particular patient and a “de novo” method for identifying tumor-specific chimeric protein-derived neoepitopes in a patient can be used and a patient-specific personalized vaccine composition can be generated.

In some embodiments, patient tumor-specific chimeric protein-derived neoepitopes (e.g., neoantigens) can be determined by sequencing RNA and/or DNA isolated from the patient's tumor biopsy sample(s) and/or normal tissue sample(s).

In some embodiments, fusion transcripts which are present in a tumor sample and absent from normal tissue are identified using established bioinformatical algorithms. In some embodiments, false positive fusion transcripts are filtered out using WGS data, homology of fused genes at RNA level, or other available approaches. In some embodiments, false positive fusion transcripts identified with in silico fusion detection are filtered out using publicly available fusion genes and fusion transcripts and chimeric proteins databases.

In some embodiments, in vitro validation of in silico detected fusion transcripts is performed using qPCR and/or Sanger sequencing with DNA and/or RNA isolated from patient's tumor sample(s) and normal tissue sample(s).

In some embodiments, a set of patient tumor-specific fusion-derived peptides corresponding to a chimeric protein's breakpoint is generated. In some embodiments, a peptide represents one or more novel tumor-specific sequences that are not presented in normal tissues and contains at least one amino acid of one fusion partner, for example from the N-terminal side or from the C-terminal side of the breakpoint, and several amino acids of the other fusion partner (e.g., from the C-terminal side or from the N-terminal side of the breakpoint).

In some embodiments, the patient is HLA genotyped using one or more in vitro techniques such as serological tests or in silico techniques based on WGS, WES or RNA sequencing data.

In some embodiments, binding affinity (or any other parameter characterizing peptide—MHC interaction process) is predicted by means of highly validated bioinformatical algorithms that can be found elsewhere including iedb.org, or cbs.dtu.dk/services/. In some embodiments, the expression level of all identified fusion transcripts corresponding to the patient's tumor-specific fusion-derived peptides are measured using RNA sequencing data or any available technique for measuring expression level of fusion transcript and/or corresponding chimeric protein. In some embodiments, the patient's tumor-specific fusion-derived neoepitopes are expression products of the fusion gene transcript and have IC₅₀ to patient's HLA proteins less than 500, less than 250, less than 150,or less than 50 nM.

In some embodiments, a patient's tumor-specific vaccine composition comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or any appropriate number of patient tumor-specific fusion-derived peptides, wherein the composition optionally comprises one or more DNA or RNA constructs encoding such peptides.

In some embodiments, a variety of bioinformatical algorithms and pipelines have been established for identifying tumor-specific fusions and generating corresponding neoepitopes.

Peptide Selection

In some embodiments, gene fusion peptides are selected based on IC₅₀ for HLA proteins. In some embodiments, gene fusion peptides having an IC₅₀ of more than 500 nM are considered non-binding. In some embodiments, peptides with an IC₅₀ of less than 500 nM are considered binding. In some embodiments, peptide vaccine compositions comprise gene fusion peptides having IC₅₀ less than 500 nM, less than 450 nM, less than 400 nM, less than 350 nM, less than 300 nM, less than 250 nM, less than 200 nM, less than 150 nM, less than 100 nM, less than 50 nM, less than 25 nM, less than 10 nM, or less than 1 nM for one or more HLA proteins of a patient are selected for a vaccine for that patient (e.g., one or more of these concentration thresholds can be used for determining peptide matches for a patient). However, other IC₅₀ thresholds (e.g., higher, lower, or intermediate concentrations) can be used to determine whether a peptide is a match for a patient.

In some embodiments, a gene fusion peptide IC₅₀ is predicted using established computational methods. In some embodiments, computational methods include NetMHC (e.g., cbs.dtu.dk/services/NetMHC/) and NetMHCpan (e.g., cbs.dtu.dk/services/NetMHCpan/). In some embodiments, a gene fusion peptide IC₅₀ is determined in vitro using one or more biochemical assays. Methods described herein are not limited by the techniques used to identify the gene fusion peptide IC₅₀.

In some embodiments, binding of gene fusion peptides to HLA proteins is determined from biological samples by eluting peptides from HLA proteins and analyzing them using mass spectrometry.

In some embodiments, gene fusion peptides are selected based on patient coverage. In some embodiments, gene fusion peptides having patient coverage greater than 5%, greater than 10%, greater than 20%, greater than 30%, greater than 40%, greater than 50%, greater than 60%, greater than 70%, greater than 80%, or greater than 90% are selected.

In some embodiments, the vaccine library can be expanded with the same methods described herein to incorporate new recurrent fusion data as it emerges.

Biological Samples

Methods provided herein detect gene fusions in biological samples. Biological samples, as used herein, refer to samples taken or derived from a patient. These samples may be tissue samples or they may be fluid samples (e.g., a bodily fluid). Examples of biological fluid samples are whole blood, plasma, serum, urine, sputum, phlegm, saliva, tears, and other bodily fluids. In some embodiments, the biological sample is a whole blood sample, or a sample of white blood cells from a subject. In some embodiments, the biological sample is a tumor, a fragment of a tumor, a tumor biopsy, or a tumor cell(s).

Treatment

Other aspects of the specification relate to methods of treatment for a patient with cancer. Cancer includes, but is not limited to: melanoma, skin cancer, head and neck cancer, breast cancer, lung cancer, ovarian cancer, cervical cancer, prostate cancer, thyroid cancer, kidney cancer, liver cancer, pancreatic cancer, gastric cancer, testicular cancer, brain tumor, glioma, glioblastoma, solitary fibrous tumor, bladder cancer, colorectal cancer, renal cell carcinoma, sarcoma, myeloma, leukemia, and/or lymphoma.

In some embodiments, the treatment is regimented to modulate the patient's immune system to induce a response against a tumor comprising a gene fusion. In some embodiments, treatment comprises administering a peptide vaccine one or more times to a patient. In some embodiments, an initial vaccine can be administered followed by one or more booster administrations. In some embodiments, a vaccine can be administered once or more daily, weekly, monthly, or at other time intervals or other frequencies. The frequency of administration and the duration of a treatment (e.g., once, one week, 1-4 weeks, 1-12 months or longer) can depend on the severity of the disease, the effectiveness of the vaccine, and/or the health of the patient. In some embodiments, treatment comprises administering a peptide vaccine at day 1, 4, 8, 15, and 21 and at week 12, 20, 30, and 40.

In some embodiments, vaccines can be administered intravenously (i.v.), intradermally (i.d.), parenterally, intraperitoneally (i.p.), subcutaneously (s.c.), intramuscularly (i.m.), orally, sublingually, intranasally, rectally, or intravaginally. The treatment is not limited to the method of vaccine administration.

In some embodiments, treatment comprises therapeutic or prophylactic vaccination of a patient with a tumor or at risk of developing cancer, and inducing antitumor immune responses in the patient. In some embodiments, treatment comprises preventive vaccination of the patient against a tumor by one or more peptides from the library or vaccine composition identified with methods described herein.

In some embodiments, treatment comprises treating a patient with a fusion-derived peptide or vaccine composition in combination with one or more additional therapies. In some embodiments, an additional therapy is an FDA approved therapy. In some embodiments, an additional therapy is an experimental therapy that is not yet approved. In some embodiments, vaccination of a patient is combined with one or more targeted therapies, chemotherapies, radiation, immunotherapy, or with hematopoietic stem cell transplantation. In some embodiments, any other suitable therapy for a particular tumor and patient may be combined with vaccination. In some embodiments, suitable therapies that can be combined with vaccination include but are not limited to immunotherapies, for example checkpoint blockade therapies, for example, but not limited to, anti-PD1 (e.g., nivolumab (Opdivo®), pembrolizumab (Keytruda®), pidilizumab etc), anti-CTLA4 (e.g., ipilimumab (Yervoy®), tremelimumab), or other checkpoint inhibitors such as BMS-936559, MPDL3280A, MEDI4736, MSB0010718C, IMP321, MGA271.

One aspect of the specification provides methods for treating a patient having a tumor and eliciting an antitumor immune response in the patient by administering dendritic cells (or other antigen presenting cells) that have been pulsed with at least one fusion-derived peptide (or coding mRNA or DNA) from the vaccine library. The dendritic cells (or other antigen presenting cells) pulsed in this manner comprise at least one fusion-derived peptide (or coding mRNA or DNA) from the vaccine library.

In some embodiments, the vaccine composition comprises at least two distinct peptides wherein each peptide corresponds to the amino acid sequence at the point of junction and each peptide is equal to or less than 50 amino acids in length.

In some embodiments, peptides or vaccine compositions are administered at concentrations sufficient to induce an antitumor immune response in the patient. Concentrations of peptides and vaccine components and dosing regimens can be easily determined by anyone skilled in the art.

In some embodiments, treatment comprises administering a vaccine having a peptide concentration of 1-10 mg per injection. In some embodiments, peptide doses per patient for one vaccination are 100 ng or more (e.g., 100-500 ng, 500-1,000 ng, or more), 1 μg or more (e.g., 1-10 μg, 10-100 μg, 100-500 μg, 500-1,000 μg, or more), 1 mg or more (e.g., 1-10 mg, 10-50 mg, 50-100 mg, or more), or 100 mg or more. In some embodiments, peptide doses per patient are adjusted depending on patient condition, patient weight, cancer stage and severity. In some embodiments, peptide doses and treatment regimen can vary depending on a patient's response to therapy. In some embodiments, peptide doses and treatment regimen can vary depending on a patient's condition.

The concentration of peptides provided in the pharmaceutical formulations can vary widely, e.g., from less than about 0.1%, usually at or at least about 2% to as much as 20% to 50% or more by weight, and will be selected primarily by fluid volumes, viscosities, etc., in accordance with the particular mode of administration selected.

In some embodiments, the peptide concentration in the vaccine (e.g., for each peptide, or the combined total peptide concentration) is around 1 nM, around 250 nM, around 500 nM, around 750 nM, around 1 around 250 around 500 around 750 around 1 mM, around 250 mM, around 500 mM, around 750 mM, or around 1M, or more or an intermediate concentration. In some embodiments, the peptide dose per patient is around 1 ng, around 250 ng, around 500 ng, around 750 ng, around 1 μg, around 250 μg, around 500 μg, around 750 μg, around 1 mg, around 250 mg, around 500 mg, around 750 mg, around 1,000 mg, or more or an intermediate amount.

In some embodiments, an initial dose is (e.g., for therapeutic or prophylactic administration) from about 1.0m to about 50,000m of peptide for a 70 kg patient, followed by subsequent doses (e.g., boosting doses) of from about 1.0m to about 10,000m of peptide pursuant to a regimen (e.g., a boosting regimen) over weeks to months depending upon the patient's response and condition. However, in some embodiments, subsequent doses can be the same as the initial dose. It should be appreciated that equivalent dosages for patients in different weight ranges can be calculated. In some embodiments, a typical dose (e.g., daily dose) is at least 0.1 μg/kg, at least 1 μg/kg, at least 10 μg/kg, at least 25 μg/kg, at least 50 μg/kg, at least 100 μg/kg, at least 250 μg/kg, at least 500 μg/kg, at least 750 μg/kg, at least 1 mg/kg, at least 10 mg/kg, or more or an intermediate range between any of these values.

In some embodiments, DNA or mRNA encoding a fusion-derived peptide or polypeptide is administered to a patient. In some embodiments, DNA or mRNA encoding a fusion-derived peptide or polypeptide is incorporated into a vector. In some embodiments, DNA or mRNA comprises additional sequences including but not limited to a T-helper sequence. In some embodiments, DNA or mRNA comprises standard regulatory sequences that ensure expression in a particular cell type. In some embodiments, DNA or mRNA comprises additional sequences encoding proteins such as IL-2 or GM-CSF that can increase a patient's immune response. In some embodiments, DNA or mRNA is transfected into mammalian cells with techniques including but not limited to electroporation.

In some embodiments, autologous T-cells can be collected from a patient and stimulated ex vivo with fusion-derived peptides and/or DNA or RNA encoding the fusion-derived peptides. In some embodiments, autologous T-cells can be collected from a patient and stimulated ex vivo with fusion-derived peptides and/or DNA or RNA encoding the fusion-derived peptides and the stimulated T-cells are infused into the patient.

In some embodiments, DNA or RNA encoding the fusion-derived peptides comprises attenuated viral vectors. In some embodiments, viral vectors comprise BCG, vaccinia, and/or fowlpox.

In some embodiments, the library can be used for treating subjects diagnosed with cancer, wherein the subject is human. In some embodiments, the subject can be a mouse, cat, dog, horse, primate, or any animal.

Use of a Therapeutic Fusion-Specific Vaccine for Treating Cancer

To practice the method disclosed herein, an effective amount of the pharmaceutical composition (e.g., vaccine) described herein can be administered to a subject (e.g., a human) in need of the treatment via a suitable route (e.g., intravenous administration, subcutaneous, intradermal, or other route).

The subject to be treated by the methods described herein can be a human patient having cancer. Examples of cancer includes, but is not limited to, melanoma, skin cancer, head and neck cancer, breast cancer, lung cancer, ovarian cancer, cervical cancer, prostate cancer, thyroid cancer, kidney cancer, liver cancer, pancreatic cancer, gastric cancer testicular cancer, brain tumor, glioma, glioblastoma, solitary fibrous tumor, bladder cancer, colorectal cancer, renal cell carcinoma, sarcoma, myeloma, leukemia, and/or lymphoma.

The subject to be treated by the methods described herein can be a mammal, more preferably a human. Mammals include, but are not limited to, farm animals, sport animals, pets, primates, horses, dogs, cats, mice and rats. A human subject who needs the treatment may be a human patient having a cancer. A subject having a cancer can be identified by routine medical examination, e.g., laboratory tests, PET scan, biopsy, PET scans, CT scans, or ultrasounds. A subject having a cancer might show one or more symptoms of the disorder, e.g., unexplained weight loss, fever, fatigue, pain, skin changes, unusual bleeding or discharge, and/or thickening or lumps in parts of the body. A subject at risk for a cancer can be a subject having one or more of the risk factors for that disorder. For example, risk factors associated with cancer include (a) viral infection (e.g., herpes virus infection), (b) age, (c) family history, (d) heavy alcohol consumption, (e) obesity, and (f) tobacco use.

“An effective amount” as used herein refers to the amount of each active agent required to confer therapeutic effect on the subject, either alone or in combination with one or more other active agents. Effective amounts vary, as recognized by those skilled in the art, depending on the particular condition being treated, the severity of the condition, the individual patient parameters including age, physical condition, size, gender and weight, the duration of the treatment, the nature of concurrent therapy (if any), the specific route of administration and like factors within the knowledge and expertise of the health practitioner. These factors are well known to those of ordinary skill in the art and can be addressed with no more than routine experimentation. It is generally preferred that a maximum dose of the individual components or combinations thereof be used, that is, the highest safe dose according to sound medical judgment. It will be understood by those of ordinary skill in the art, however, that a patient may insist upon a lower dose or tolerable dose for medical reasons, psychological reasons or for virtually any other reasons.

Empirical considerations, such as the half-life, generally will contribute to the determination of the dosage. For example, antibodies that are compatible with the human immune system, such as humanized antibodies or fully human antibodies, may be used to prolong half-life of the peptide and to prevent the peptide being attacked by the host's immune system. Frequency of administration may be determined and adjusted over the course of therapy, and is generally, but not necessarily, based on treatment and/or suppression and/or amelioration and/or delay of a cancer. Alternatively, sustained continuous release formulations of a fusion-specific vaccine may be appropriate. Various formulations and devices for achieving sustained release are known in the art.

In one example, dosages for a fusion-specific vaccine as described herein may be determined empirically in individuals who have been given one or more administration(s) of a fusion-specific vaccine. Individuals are given incremental dosages of the fusion-specific vaccine. To assess efficacy of the fusion-specific vaccine, an indicator of a cancer (such as tumor formation or tumor growth) can be followed.

In some embodiments, dosing frequency is once every week, every 2 weeks, every 4 weeks, every 5 weeks, every 6 weeks, every 7 weeks, every 8 weeks, every 9 weeks, or every 10 weeks; or once every month, every 2 months, or every 3 months, or longer. The progress of this therapy is easily monitored by conventional techniques and assays. The dosing regimen (including the fusion-specific vaccine used) can vary over time. For repeated administrations over several days or longer, depending on the condition, the treatment is sustained until a desired suppression of symptoms occurs or until sufficient therapeutic levels are achieved to alleviate a cancer, or a symptom thereof.

For the purpose of the present disclosure, the appropriate dosage of a fusion-specific vaccine will depend on the specific fusion-specific vaccine(s) (or compositions thereof) employed, the type and severity of cancer, whether the fusion-specific vaccine is administered for preventive or therapeutic purposes, previous therapy, the patient's clinical history and response to the antagonist, and the discretion of the attending physician. Typically the clinician will administer a fusion-specific vaccine, until a dosage is reached that achieves the desired result. Administration of a fusion-specific vaccine can be continuous or intermittent, depending, for example, upon the recipient's physiological condition, whether the purpose of the administration is therapeutic or prophylactic, and other factors known to skilled practitioners. The administration of a fusion-specific vaccine may be essentially continuous over a preselected period of time or may be in a series of spaced dose, e.g., either before, during, or after developing cancer.

As used herein, the term “treating” refers to the application or administration of a composition including one or more active agents to a subject, who has a cancer, a symptom of a cancer, or a predisposition toward a cancer, with the purpose to cure, heal, alleviate, relieve, alter, remedy, ameliorate, improve, or affect the disorder, the symptom of the disease, or the predisposition toward a cancer.

Alleviating a cancer includes delaying the development or progression of the disease, or reducing disease severity. Alleviating the disease does not necessarily require curative results. As used therein, “delaying” the development of a disease (such as lung cancer) means to defer, hinder, slow, retard, stabilize, and/or postpone progression of the disease. This delay can be of varying lengths of time, depending on the history of the disease and/or individuals being treated. A method that “delays” or alleviates the development of a disease, or delays the onset of the disease, is a method that reduces probability of developing one or more symptoms of the disease in a given time frame and/or reduces extent of the symptoms in a given time frame, when compared to not using the method. Such comparisons are typically based on clinical studies, using a number of subjects sufficient to give a statistically significant result.

“Development” or “progression” of a disease means initial manifestations and/or ensuing progression of the disease. Development of the disease can be detectable and assessed using standard clinical techniques as well known in the art. However, development also refers to progression that may be undetectable. For purpose of this disclosure, development or progression refers to the biological course of the symptoms. “Development” includes occurrence, recurrence, and onset. As used herein “onset” or “occurrence” of a cancer includes initial onset and/or recurrence.

In some embodiments, the fusion-specific vaccine described herein is administered to a subject in need of the treatment at an amount sufficient to induce a immunological response against a tumor by at least 5% (e.g., 15%, 30%, 40%, 50%, 60%, 70%, 80%, 90% or greater). In other embodiments, the fusion-specific vaccine is administered in an amount effective in reducing tumor metastasis. Alternatively, the fusion-specific vaccine is administered in an amount effective in reducing tumor formation or tumor growth.

Conventional methods, known to those of ordinary skill in the art of medicine, can be used to administer the pharmaceutical composition to the subject, depending upon the type of disease to be treated or the site of the disease. This composition can also be administered via other conventional routes, e.g., administered orally, parenterally, by inhalation spray, topically, rectally, nasally, buccally, vaginally or via an implanted reservoir. The term “parenteral” as used herein includes subcutaneous, intracutaneous, intravenous, intramuscular, intraarticular, intraarterial, intrasynovial, intrasternal, intrathecal, intralesional, and intracranial injection or infusion techniques. In addition, it can be administered to the subject via injectable depot routes of administration such as using 1-, 3-, or 6-month depot injectable or biodegradable materials and methods.

Injectable compositions may contain various carriers such as vegetable oils, dimethylactamide, dimethyformamide, ethyl lactate, ethyl carbonate, isopropyl myristate, ethanol, and polyols (glycerol, propylene glycol, liquid polyethylene glycol, and the like). For intravenous injection, water soluble antibodies can be administered by the drip method, whereby a pharmaceutical formulation containing the antibody and a physiologically acceptable excipients is infused. Physiologically acceptable excipients may include, for example, 5% dextrose, 0.9% saline, Ringer's solution or other suitable excipients. Intramuscular preparations, e.g., a sterile formulation of a suitable soluble salt form of the antibody, can be dissolved and administered in a pharmaceutical excipient such as Water-for-Injection, 0.9% saline, or 5% glucose solution.

In one embodiment, a fusion-specific vaccine is administered via site-specific or targeted local delivery techniques. Examples of site-specific or targeted local delivery techniques include various implantable depot sources of the fusion-specific vaccine or local delivery catheters, such as infusion catheters, an indwelling catheter, or a needle catheter, synthetic grafts, adventitial wraps, shunts and stents or other implantable devices, site specific carriers, direct injection, or direct application. See, e.g., PCT Publication No. WO 00/53211 and U.S. Pat. No. 5,981,568.

Targeted delivery of therapeutic compositions containing a polynucleotide, expression vector, or subgenomic polynucleotides can also be used. Receptor-mediated DNA delivery techniques are described in, for example, Findeis et al., Trends Biotechnol. (1993) 11:202; Chiou et al., Gene Therapeutics: Methods And Applications Of Direct Gene Transfer (J. A. Wolff, ed.) (1994); Wu et al., J. Biol. Chem. (1988) 263:621; Wu et al., J. Biol. Chem. (1994) 269:542; Zenke et al., Proc. Natl. Acad. Sci. USA (1990) 87:3655; Wu et al., J. Biol. Chem. (1991) 266:338. Therapeutic compositions containing a polynucleotide are administered in a range of about 100 ng to about 200 mg of DNA for local administration in a gene therapy protocol. In some embodiments, concentration ranges of about 500 ng to about 50 mg, about 1 μg to about 2 mg, about 5 μg to about 500 μg, and about 20 μg to about 100 μg of DNA or more can also be used during a gene therapy protocol.

The therapeutic polynucleotides and polypeptides described herein can be delivered using gene delivery vehicles. The gene delivery vehicle can be of viral or non-viral origin (see generally, Jolly, Cancer Gene Therapy (1994) 1:51; Kimura, Human Gene Therapy (1994) 5:845; Connelly, Human Gene Therapy (1995) 1:185; and Kaplitt, Nature Genetics (1994) 6:148). Expression of such coding sequences can be induced using endogenous mammalian or heterologous promoters and/or enhancers. Expression of the coding sequence can be either constitutive or regulated.

Viral-based vectors for delivery of a desired polynucleotide and expression in a desired cell are well known in the art. Exemplary viral-based vehicles include, but are not limited to, recombinant retroviruses (see, e.g., PCT Publication Nos. WO 90/07936; WO 94/03622; WO 93/25698; WO 93/25234; WO 93/11230; WO 93/10218; WO 91/02805; U.S. Pat. Nos. 5,219,740 and 4,777,127; GB Patent No. 2,200,651; and EP Patent No. 0 345 242), alphavirus-based vectors (e.g., Sindbis virus vectors, Semliki forest virus (ATCC VR-67; ATCC VR-1247), Ross River virus (ATCC VR-373; ATCC VR-1246) and Venezuelan equine encephalitis virus (ATCC VR-923; ATCC VR-1250; ATCC VR 1249; ATCC VR-532)), and adeno-associated virus (AAV) vectors (see, e.g., PCT Publication Nos. WO 94/12649, WO 93/03769; WO 93/19191; WO 94/28938; WO 95/11984 and WO 95/00655). Administration of DNA linked to killed adenovirus as described in Curiel, Hum. Gene Ther. (1992) 3:147 can also be employed.

Non-viral delivery vehicles and methods can also be employed, including, but not limited to, polycationic condensed DNA linked or unlinked to killed adenovirus alone (see, e.g., Curiel, Hum. Gene Ther. (1992) 3:147); ligand-linked DNA (see, e.g., Wu, J. Biol. Chem. (1989) 264:16985); eukaryotic cell delivery vehicles cells (see, e.g., U.S. Pat. No. 5,814,482; PCT Publication Nos. WO 95/07994; WO 96/17072; WO 95/30763; and WO 97/42338) and nucleic charge neutralization or fusion with cell membranes. Naked DNA can also be employed. Exemplary naked DNA introduction methods are described in PCT Publication No. WO 90/11092 and U.S. Pat. No. 5,580,859. Liposomes that can act as gene delivery vehicles are described in U.S. Pat. No. 5,422,120; PCT Publication Nos. WO 95/13796; WO 94/23697; WO 91/14445; and EP Patent No. 0524968. Additional approaches are described in Philip, Mol. Cell. Biol. (1994) 14:2411, and in Woffendin, Proc. Natl. Acad. Sci. (1994) 91:1581.

It is also apparent that an expression vector can be used to direct expression of any of the fusion-specific vaccines described herein. The particular dosage regimen, i.e., dose, timing and repetition, used in the method described herein will depend on the particular subject and that subject's medical history.

In some embodiments, more than one fusion-specific vaccine may be administered to a subject in need of the treatment. The fusion-specific vaccine can correspond to the same tumor junction sequence or different tumor junction sequences. At least one, at least two, at least three, at least four, at least five different fusion-specific vaccines can be co-administered. Generally, those fusion-specific vaccines have complementary activities that do not adversely affect each other. Fusion-specific vaccines can also be used in conjunction with other agents that serve to enhance and/or complement the effectiveness of the agents.

Treatment efficacy can be assessed by methods well-known in the art, e.g., monitoring tumor growth or formation in a patient subjected to the treatment.

Combination Therapy

Also provided herein are combined therapies using any of the fusion-specific vaccines described herein and another anti-cancer therapeutic agent, such as those described herein. The term combination therapy, as used herein, embraces administration of these agents (e.g., a fusion-specific vaccine and an anti-cancer therapeutic agent) in a sequential manner, that is, wherein each therapeutic agent is administered at a different time, as well as administration of these therapeutic agents, or at least two of the agents, in a substantially simultaneous manner. In some embodiments, combination therapies include two or more therapeutic agents (e.g., vaccines or other agents) combined in the same composition. However, in many embodiments, different therapeutic agents are provided in separate compositions. Sequential or substantially simultaneous administration of each agent can be affected by any appropriate route including, but not limited to, oral routes, intravenous routes, intramuscular, subcutaneous routes, and direct absorption through mucous membrane tissues. The agents can be administered by the same route or by different routes. For example, a first agent (e.g., a fusion-specific vaccine) can be administered orally, and a second agent (e.g., an anti-cancer agent) can be administered intravenously.

As used herein, the term “sequential” means, unless otherwise specified, characterized by a regular sequence or order, e.g., if a dosage regimen includes the administration of a fusion-specific vaccine and an anti-cancer agent, a sequential dosage regimen could include administration of the fusion-specific vaccine before, simultaneously, substantially simultaneously, or after administration of the anti-cancer agent, but both agents will be administered in a regular sequence or order. The term “separate” means, unless otherwise specified, to keep apart one from the other. The term “simultaneously” means, unless otherwise specified, happening or done at the same time, i.e., the agents of the invention are administered at the same time. The term “substantially simultaneously” means that the agents are administered within minutes of each other (e.g., within 10 minutes of each other) and intends to embrace joint administration as well as consecutive administration, but if the administration is consecutive it is separated in time for only a short period (e.g., the time it would take a medical practitioner to administer two agents separately). As used herein, concurrent administration and substantially simultaneous administration are used interchangeably. Sequential administration refers to temporally separated administration of the agents described herein.

Combination therapy can also embrace the administration of the agents described herein (e.g., a fusion-specific vaccine and an anti-cancer agent) in further combination with other biologically active ingredients (e.g., a different anti-cancer agent) and non-drug therapies (e.g., surgery).

It should be appreciated that any combination of a fusion-specific vaccine and another anti-cancer agent (e.g., a chemotherapeutic agent) may be used in any sequence for treating a cancer. The combinations described herein may be selected on the basis of a number of factors, which include but are not limited to the effectiveness of inducing an immune response, reducing tumor formation or tumor growth, and/or alleviating at least one symptom associated with the cancer, or the effectiveness for mitigating the side effects of another agent of the combination. For example, a combined therapy described herein may reduce any of the side effects associated with each individual members of the combination, for example, a side effect associated with the anti-cancer agent.

In some embodiments, another anti-cancer therapeutic agent is a chemotherapy, a radiation therapy, a surgical therapy and/or an immunotherapy. Examples of the chemotherapeutic agents include, but are not limited to, Carboplatin or Cisplatin, Docetaxel, Gemcitabine, Nab-Paclitaxel, Paclitaxel, Pemetrexed, and Vinorelbine. Examples of radiation therapy include, but are not limited to, ionizing radiation, gamma-radiation, neutron beam radiotherapy, electron beam radiotherapy, proton therapy, brachytherapy, and systemic radioactive isotopes and radiosensitizers. Examples of a surgical therapy include, but are not limited to, a curative surgery (e.g., tumor removal surgery), a preventive surgery, a laparoscopic surgery, and a laser surgery. Examples of an immunotherapy include, but are not limited to, a PD-1 inhibitor or a PD-L1 inhibitor, adoptive cell transfer, and therapeutic cancer vaccines.

Additional examples of chemotherapy include, but are not limited to, Platinating agents, such as Carboplatin, Oxaliplatin, Cisplatin, Nedaplatin, Satraplatin, Lobaplatin, Triplatin, Tetranitrate, Picoplatin, Prolindac, Aroplatin and other derivatives; Topoisomerase I inhibitors, such as Camptothecin, Topotecan, irinotecan/SN38, rubitecan, Belotecan, and other derivatives; Topoisomerase II inhibitors, such as Etoposide (VP-16), Daunorubicin, a doxorubicin agent (e.g., doxorubicin, doxorubicin HCl, doxorubicin analogs, or doxorubicin and salts or analogs thereof in liposomes), Mitoxantrone, Aclarubicin, Epirubicin, Idarubicin, Amrubicin, Amsacrine, Pirarubicin, Valrubicin, Zorubicin, Teniposide and other derivatives; Antimetabolites, such as Folic family (Methotrexate, Pemetrexed, Raltitrexed, Aminopterin, and relatives); Purine antagonists (Thioguanine, Fludarabine, Cladribine, 6-Mercaptopurine, Pentostatin, clofarabine and relatives) and Pyrimidine antagonists (Cytarabine, Floxuridine, Azacitidine, Tegafur, Carmofur, Capacitabine, Gemcitabine, hydroxyurea, 5-Fluorouracil (5FU), and relatives); Alkylating agents, such as Nitrogen mustards (e.g., Cyclophosphamide, Melphalan, Chlorambucil, mechlorethamine, Ifosfamide, mechlorethamine, Trofosfamide, Prednimustine, Bendamustine, Uramustine, Estramustine, and relatives); nitrosoureas (e.g., Carmustine, Lomustine, Semustine, Fotemustine, Nimustine, Ranimustine, Streptozocin, and relatives); Triazenes (e.g., Dacarbazine, Altretamine, Temozolomide, and relatives); Alkyl sulphonates (e.g., Busulfan, Mannosulfan, Treosulfan, and relatives); Procarbazine; Mitobronitol, and Aziridines (e.g., Carboquone, Triaziquone, ThioTEPA, triethylenemalamine, and relatives); Antibiotics, such as Hydroxyurea, Anthracyclines (e.g., doxorubicin agent, daunorubicin, epirubicin and other derivatives); Anthracenediones (e.g., Mitoxantrone and relatives); Streptomyces family (e.g., Bleomycin, Mitomycin C, Actinomycin, Plicamycin); and Ultraviolet light.

Pharmaceutical Compositions

In some embodiments, methods are provided for constructing a fusion-derived vaccine library which can be used for treating a patient having cancer and eliciting an immune response in the patient. In some embodiments, the vaccine comprises fusion-derived long peptides or polypeptides comprising neoantigens peptides matched to patients HLA and which can induce an antitumor immune response in the patient. In some embodiments, the immune response can be detected by analyzing IFN-γ production or tumor killing activity of T-cells in vitro.

In some embodiments, the vaccine comprises one fusion-derived long peptide at a breakpoint or several shorter derivatives of the long peptide. In some embodiments, the vaccine comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 neoantigenic peptides that can be bound by the patient's HLA class I and/or class II proteins. It should be appreciated that the vaccine comprising one or more neoantigenic peptides may further comprise one or more additional therapeutic agents. Alternatively, or in addition, on or more additional therapeutic agents may be administered separately

In some embodiments, a vaccine comprises two or more different peptides that are selected for a patient, wherein the peptide are mixed together in a single vaccine composition for administration to the patient. However, in some embodiments, two or more different peptides can be administered separately to a patient. It should be appreciated that a vaccine can contain any suitable concentration of each of the two or more peptides. In some embodiments, the concentration of each peptide in the vaccine is identical or similar. However, in some embodiments, different peptides can be provided at different concentrations.

In some embodiments, the vaccine comprises fusion-derived long peptides or polypeptides that are processed into shorter neoantigenic peptides which can be bound to at least one HLA class I protein of the patient. In some embodiments, the vaccine comprises fusion-derived long peptides or polypeptides that are processed into shorter neoantigenic peptides which can be bound to one or more, two or more, three or more, four or more, five or more, or six HLA class I protein of the patient. In some embodiments, peptides can bind to HLA class II proteins and induce helper T-cell response.

In some embodiments, a vaccine comprises several different fusion-derived long peptides or polypeptides corresponding to several different fusion genes present in the patient's tumor. In some embodiments, compositions comprises one or more, or two or more neoantigenic fusion-derived peptides.

In some embodiments, vaccine compositions comprises any adjuvant that can be used to activate an immune response in a patient. In some embodiments, an adjuvant can be any substance or any compound incorporated into a vaccine composition that increases the immune response of the patient to the fusion-derived peptides. Examples of adjuvants include, but are not limited to, poly-ICLC, Poly (I:C), GM-CSF, BCG, monophosphoryl lipid A, MF59, Freund's adjuvants, Montanide IMS, Montanide ISA 206, Montanide ISA-51, Montanide ISA 50V, Aluminium salts, Alhydrogel, Rehydrogel HPA, PLGA, MPL1, AS04, AS01B, AS02A, P3CSK4, CpG-ODN, Imiquimod ISS, ONTAK, LipoVac, Amplivax, CpG7909, dSLIM, IC30, IC31, SRL172, virus particles, YF-17D, AS15, OK-432, IMP321, OM-174, cytokines, and other adjuvants that can be found in the field using any source (e.g., peer-reviewed literature or medical guidelines).

In some embodiments, fusion-derived peptides are administered separately from one or more adjuvant(s). In some embodiments, fusion-derived peptides are administered along with one or more adjuvant(s). In some embodiments, vaccine compositions comprise one or more adjuvants and one or more fusion-derived peptides.

In some embodiments, vaccine compositions comprise different carriers such as polysaccharides, polypeptides, proteins, liposomes, or antigen presenting cells. In some embodiments, peptides might be combined with carriers that increase their immunogenicity, biological activity, and/or stability. In some embodiments, carriers include, but are not limited to, proteins such as bovine serum albumin (BSA), human serum albumin, immunoglobulins, transferrin, insulin; and/or carbohydrates such as lactose, cellulose, starch. In some embodiments, carriers are proteins such as diphtheria toxoid, tetanus toxoid, influenza virus proteins, and/or herpes virus proteins. In some embodiments, vaccine compositions comprise any carriers that are safe and acceptable for patients.

In some embodiments, vaccine compositions comprise at least one or more autologous antigen presenting cells (APC) pulsed with respective fusion-derived peptides from library. Pulsing APC cells may be performed in any manner known in the field. See, for example, Boczkowski et al, J Exp. Med. 1996 Aug. 1; 184(2): 465-72; see also: O'Neill and Bhardwaj, Adoptive Immunotherapy: Methods and Protocols, 2005, Volume 109 pp 97-112, which are incorporated by reference herein for this purpose. In some embodiments, vaccine compositions comprise at least one or more autologous antigen presenting cells (APC) comprising fusion-derived peptides from library. In some embodiments, APCs can be dendritic cells, macrophages, B-cells, or any professional antigen presenting cell. In some embodiments, APCs can be loaded with DNA or mRNA encoding respective fusion-derived peptide(s) of a vaccine library. In some embodiments, vaccine compositions comprise autologous peripheral blood mononuclear cells (PBMC).

In another aspect, vaccine compositions comprise components directed to the personal needs of a particular patient. In some embodiments, the personal needs of a particular patient include but are not limited to allergies, previous treatments, and/or comorbidities.

In some embodiments, fusion-derived peptides from a library can be combined with any other tumor-specific neoantigens for a particular patient that are not included in the vaccine library. In some embodiments, fusion-derived peptides from a library can be combined with tumor-specific neoantigens for a particular patient that have been identified de novo from WGS, WES, or RNA sequencing data.

In some embodiments, vaccine compositions can be prepared in sterilized water. In some embodiments, vaccine compositions can be prepared in buffered solutions such as but not limited to 0.9% saline.

One or more of the fusion-specific vaccines provided herein can be mixed with a pharmaceutically acceptable carrier (excipient), including buffer, to form a pharmaceutical composition for use in treating cancer. “Acceptable” means that the carrier must be compatible with the active ingredient of the composition (and preferably, capable of stabilizing the active ingredient) and not deleterious to the subject to be treated. Pharmaceutically acceptable excipients (carriers) including buffers, which are well known in the art. See, e.g., Remington: The Science and Practice of Pharmacy 20th Ed. (2000) Lippincott Williams and Wilkins, Ed. K. E. Hoover.

For example, a pharmaceutical composition described herein contains one or more fusion-specific vaccines that correspond to one or more tumor-specific gene fusions. In one example, a pharmaceutical composition described herein contains more than one fusion-specific vaccines that recognize a tumor-specific gene fusion. In another example, the pharmaceutical composition comprises at least two fusion-specific vaccines that correspond to different tumor-specific gene fusions. Alternatively or in addition, the pharmaceutical composition comprises one or more peptide vaccines or other anticancer agents. It should be appreciated that any of the pharmaceutical compositions provided herein may be administered alone, separately or in a combination.

The pharmaceutical compositions to be used in the present methods can comprise pharmaceutically acceptable carriers, excipients, or stabilizers in the form of lyophilized formulations or aqueous solutions. (Remington: The Science and Practice of Pharmacy 20^(th) Ed. (2000) Lippincott Williams and Wilkins, Ed. K. E. Hoover). Acceptable carriers, excipients, or stabilizers are nontoxic to recipients at the dosages and concentrations used, and may comprise buffers such as phosphate, citrate, and other organic acids; antioxidants including ascorbic acid and methionine; preservatives (such as octadecyldimethylbenzyl ammonium chloride; hexamethonium chloride; benzalkonium chloride, benzethonium chloride; phenol, butyl or benzyl alcohol; alkyl parabens such as methyl or propyl paraben; catechol; resorcinol; cyclohexanol; 3-pentanol; and m-cresol); low molecular weight (less than about 10 residues) polypeptides; proteins, such as serum albumin, gelatin, or immunoglobulins; hydrophilic polymers such as polyvinylpyrrolidone; amino acids such as glycine, glutamine, asparagine, histidine, arginine, or lysine; monosaccharides, disaccharides, and other carbohydrates including glucose, mannose, or dextrans; chelating agents such as EDTA; sugars such as sucrose, mannitol, trehalose or sorbitol; salt-forming counter-ions such as sodium; metal complexes (e.g., Zn-protein complexes); and/or non-ionic surfactants such as TWEEN™ (polysorbate), PLURONICS™ (poloxamers) or polyethylene glycol (PEG). Pharmaceutically acceptable excipients are further described herein.

In some examples, the pharmaceutical composition described herein comprises liposomes containing the fusion-specific vaccine, which can be prepared by methods known in the art, such as described in Epstein, et al., Proc. Natl. Acad. Sci. USA 82:3688 (1985); Hwang, et al., Proc. Natl. Acad. Sci. USA 77:4030 (1980); and U.S. Pat. Nos. 4,485,045 and 4,544,545. Liposomes with enhanced circulation time are disclosed in U.S. Pat. No. 5,013,556. Particularly useful liposomes can be generated by the reverse phase evaporation method with a lipid composition comprising phosphatidylcholine, cholesterol and PEG-derivatized phosphatidylethanolamine (PEG-PE). Liposomes are extruded through filters of defined pore size to yield liposomes with the desired diameter.

The active ingredients (e.g., a fusion-specific vaccine) may also be entrapped in microcapsules prepared, for example, by coacervation techniques or by interfacial polymerization, for example, hydroxymethylcellulose or gelatin-microcapsules and poly-(methylmethacylate) microcapsules, respectively, in colloidal drug delivery systems (for example, liposomes, albumin microspheres, microemulsions, nano-particles and nanocapsules) or in macroemulsions. Such techniques are known in the art, see, e.g., Remington, The Science and Practice of Pharmacy 20th Ed. Mack Publishing (2000).

In other examples, the pharmaceutical composition described herein can be formulated in sustained-release format. Suitable examples of sustained-release preparations include semipermeable matrices of solid hydrophobic polymers containing the antibody, which matrices are in the form of shaped articles, e.g., films, or microcapsules. Examples of sustained-release matrices include polyesters, hydrogels (for example, poly(2-hydroxyethyl-methacrylate), or poly(vinylalcohol)), polylactides (U.S. Pat. No. 3,773,919), copolymers of L-glutamic acid and 7 ethyl-L-glutamate, non-degradable ethylene-vinyl acetate, degradable lactic acid-glycolic acid copolymers such as the LUPRON DEPOT™ (injectable microspheres composed of lactic acid-glycolic acid copolymer and leuprolide acetate), sucrose acetate isobutyrate, and poly-D-(−)-3-hydroxybutyric acid.

The pharmaceutical compositions to be used for in vivo administration must be sterile. This is readily accomplished by, for example, filtration through sterile filtration membranes. However, other sterilization techniques, including but not limited to heat, chemical, and/or radiation based sterilization techniques may be used. Therapeutic vaccine compositions are generally placed into a container having a sterile access port, for example, an intravenous solution bag or vial having a stopper pierceable by a hypodermic injection needle.

The pharmaceutical compositions described herein can be in unit dosage forms such as tablets, pills, capsules, powders, granules, solutions or suspensions, or suppositories, for oral, parenteral or rectal administration, or administration by inhalation or insufflation.

For preparing solid compositions such as tablets, the principal active ingredient can be mixed with a pharmaceutical carrier, e.g. conventional tableting ingredients such as corn starch, lactose, sucrose, sorbitol, talc, stearic acid, magnesium stearate, dicalcium phosphate or gums, and other pharmaceutical diluents, e.g. water, to form a solid preformulation composition containing a homogeneous mixture of a compound of the present invention, or a non-toxic pharmaceutically acceptable salt thereof. When referring to these preformulation compositions as homogeneous, it is meant that the active ingredient is dispersed evenly throughout the composition so that the composition may be readily subdivided into equally effective unit dosage forms such as tablets, pills and capsules. This solid preformulation composition is then subdivided into unit dosage forms of the type described herein containing from 0.1 to about 500 mg of the active ingredient of the present invention. The tablets or pills of the novel composition can be coated or otherwise compounded to provide a dosage form affording the advantage of prolonged action. For example, the tablet or pill can comprise an inner dosage and an outer dosage component, the latter being in the form of an envelope over the former. The two components can be separated by an enteric layer that serves to resist disintegration in the stomach and permits the inner component to pass intact into the duodenum or to be delayed in release. A variety of materials can be used for such enteric layers or coatings, such materials including a number of polymeric acids and mixtures of polymeric acids with such materials as shellac, cetyl alcohol and cellulose acetate.

Suitable surface-active agents include, in particular, non-ionic agents, such as polyoxyethylenesorbitans (e.g., Tween™ 20, 40, 60, 80 or 85) and other sorbitans (e.g., Span™ 20, 40, 60, 80 or 85). Compositions with a surface-active agent will conveniently comprise between 0.05 and 5% surface-active agent, and can be between 0.1 and 2.5%. It will be appreciated that other ingredients may be added, for example mannitol or other pharmaceutically acceptable vehicles, if necessary.

Suitable emulsions may be prepared using commercially available fat emulsions, such as Intralipid™, Liposyn™, Infonutrol™, Lipofundin™ and Lipiphysan™. The active ingredient may be either dissolved in a pre-mixed emulsion composition or alternatively it may be dissolved in an oil (e.g., soybean oil, safflower oil, cottonseed oil, sesame oil, corn oil or almond oil) and an emulsion formed upon mixing with a phospholipid (e.g., egg phospholipids, soybean phospholipids or soybean lecithin) and water. It will be appreciated that other ingredients may be added, for example glycerol or glucose, to adjust the tonicity of the emulsion. Suitable emulsions will typically contain up to 20% oil, for example, between 5 and 20%. The fat emulsion can comprise fat droplets between 0.1 and 1.0 .im, particularly 0.1 and 0.5 .im, and have a pH in the range of 5.5 to 8.0.

The emulsion compositions can be those prepared by mixing a fusion-specific vaccine with Intralipid™ (a lipid emulsion) or the components thereof (soybean oil, egg phospholipids, glycerol and water).

Pharmaceutical compositions for inhalation or insufflation include solutions and suspensions in pharmaceutically acceptable, aqueous or organic solvents, or mixtures thereof, and powders. The liquid or solid compositions may contain suitable pharmaceutically acceptable excipients as set out above. In some embodiments, the compositions are administered by the oral or nasal respiratory route for local or systemic effect.

Compositions in preferably sterile pharmaceutically acceptable solvents may be nebulised by use of gases. Nebulised solutions may be breathed directly from the nebulising device or the nebulising device may be attached to a face mask, tent or intermittent positive pressure breathing machine. Solution, suspension or powder compositions may be administered, preferably orally or nasally, from devices which deliver the formulation in an appropriate manner.

Kits for Use in Treating Cancer

The present disclosure also provides kits for use in alleviating cancer. Such kits can include one or more containers comprising a fusion-specific vaccine. In some embodiments, the kit can comprise instructions for use in accordance with any of the methods described herein. The included instructions can comprise a description of administration of the fusion-specific vaccine to treat, delay the onset, or alleviate a cancer according to any of the methods described herein. The kit may further comprise a description of selecting an individual suitable for treatment based on identifying whether that individual has cancer. In still other embodiments, the instructions comprise a description of administering a fusion-specific vaccine to an individual having, suspected of having, or at risk for a cancer.

The instructions relating to the use of a fusion-specific vaccine generally include information as to dosage, dosing schedule, and route of administration for the intended treatment. The containers may be unit doses, bulk packages (e.g., multi-dose packages) or sub-unit doses. Instructions supplied in the kits of the invention are typically written instructions on a label or package insert (e.g., a paper sheet included in the kit), but machine-readable instructions (e.g., instructions carried on a magnetic or optical storage disk) are also acceptable.

The label or package insert indicates that the composition is used for treating, delaying the onset and/or alleviating a cancer. Instructions may be provided for practicing any of the methods described herein.

The kits of this invention are in suitable packaging. Suitable packaging includes, but is not limited to, vials, bottles, jars, flexible packaging (e.g., sealed Mylar or plastic bags), and the like. Also contemplated are packages for use in combination with a specific device, such as an inhaler, nasal administration device (e.g., an atomizer) or an infusion device such as a minipump. A kit may have a sterile access port (for example the container may be an intravenous solution bag or a vial having a stopper pierceable by a hypodermic injection needle). The container may also have a sterile access port (for example the container may be an intravenous solution bag or a vial having a stopper pierceable by a hypodermic injection needle). At least one active agent in the composition is a fusion-specific vaccine.

Kits may optionally provide additional components such as buffers and interpretive information. Normally, the kit comprises a container and a label or package insert(s) on or associated with the container. In some embodiments, the invention provides articles of manufacture comprising contents of the kits described herein.

Without further elaboration, it is believed that one skilled in the art can, based on the description herein, utilize the present invention to its fullest extent. The following specific embodiments are, therefore, to be construed as merely illustrative, and not limitative of the remainder of the disclosure in any way whatsoever. All publications cited herein are incorporated by reference for the purposes or subject matter referenced herein.

Computational Methods

It should be appreciated that the various aspects and concepts of the present methods described herein may be implemented in any of numerous ways, and are not limited to any particular implementation technique. Examples of specific implementations are described below for illustrative purposes only, but the aspects of the methods described herein are not limited to these illustrative implementations.

FIG. 5 shows a non-limiting illustrative environment 500 in which embodiments of the present methods may operate. In the illustrative environment, healthcare provider 502 may use any device 504 to obtain information from system 510. Healthcare provider 502 may obtain information from system 510 one time or multiple times. Information between healthcare provider 502 and system 510 may be initiated in any suitable way.

In some embodiments, device 504 may be any suitable device that healthcare provider 502 may use to obtain information from system 510. For instance, device 504 may be a dedicated mobile phone (e.g., a cellular phone), a mobile smart phone, a personal digital assistant (PDA), a laptop computer, a tablet computer, or any other mobile device capable of supporting an exchange of information through a communications medium (e.g., a wired or wireless communications medium). In some embodiments, healthcare provider 502 is not limited to obtaining information by using a mobile device and may use any device capable of obtaining information. For instance, healthcare provider 502 may obtain information from 510 by using a telephone connected to landline, a desktop computer connected to a network such as the Internet, or using any other device capable of communicating with system 510. It should also be recognized that if healthcare provider 502 obtains information from system 510, healthcare provider 502 is not limited to using the same device. Thus, healthcare provider 502 may obtain information using one or a plurality of different devices, each of which may be any suitable device capable of obtaining information.

Information may be any suitable information relating to patient data and/or library data. Information is not limited by the type of communications infrastructure or communications medium used to obtain the information. For example, information may be patient information such as but not limited to a patient's identity, cancer type, gene fusion, and/or HLA allele information. As another example, information may be library information such as but not limited to peptide sequence information, peptide-HLA affinities, sequences of DNA and/or RNA encoding peptide sequence information, and/or gene fusion information.

In the illustrated embodiment, device 504 communicates with system 510 through a communication medium 508. Communication medium 508 may be any suitable network or other type of communication medium. For example, communication medium 508 may be a cellular network, a local area network, a circuit-switched telephone network, a public-switched telephone network, the Internet, some combination of any of the foregoing, or any other communication medium capable of supporting telecommunications.

In the illustrated embodiment, device 504 is communicatively coupled to communication medium 508 via wireless connection 506 and system 510 is communicatively coupled to communication medium 508 using a wired connection 516. This is merely for illustration, as device 504 and system 510 each may be communicatively coupled to communication medium 508 in any suitable way including wired and/or wireless connections.

System 510 comprises one or more computers (e.g., servers) each configured to perform processing related to supporting matching patient data and library data. In the illustrated embodiment, system 510 comprises a single server 512, though in other embodiments any suitable number of servers may be used and distributed in any manner. For instance, in some embodiments, system 510 may comprise at least ten, at least one hundred, at least one thousand, or at least ten thousand servers. For embodiments in which system 510 comprises multiple servers, the servers need not be located in the same physical location and may be distributed across multiple physical locations.

Each server, such as server 512, may be configured (alone or in combination with one or more other servers) to support one or more applications and may be configured to execute any other programs. For example, one or more of the servers may be configured to execute programs for supporting functionality related to patient data, library data, patient and library matching, and/or any other functions used in embodiments of the present methods.

As previously discussed, a healthcare provider, such as healthcare provider 502, may conduct one or multiple analyses with system 510. Multiple analyses may take place over any suitable time period of any suitable length. In some embodiments, system 510 calculates HLA-peptide affinities. In some embodiments, system 510 calculates HLA-peptide matching and a healthcare provider obtains this information. In some embodiments, a healthcare provider receives matched HLA-peptide information from system 510.

As discussed herein, system 510 may obtain any suitable data associated with one or more healthcare providers (e.g., information identifying healthcare provider 502, patient information, library information, patient and library matching information, etc.). System 510 may obtain any of the above-described data, associated with one or more healthcare providers, in any suitable way. For example, system 510 may extract this data from information collected from healthcare provider 502. In this case, system 510 may store at least a portion of the obtained data on one or more storage devices 516 so that it may be retrieved from the one or more storage devices for subsequent use as discussed herein.

Storage device(s) 516 may be any suitable storage device(s) or article(s) of manufacture capable of storing information. For example, storage device(s) 516 may be any non-transitory computer readable storage medium or media such as a computer memory (RAM and/or ROM), one or more hard disk drives, one or more optical disks (CDs and/or DVDs), one or more magnetic tapes, one or more flash memories, one or more circuit configurations in Field Programmable Gate Arrays and/or any other suitable device(s).

In the illustrated embodiment, storage device(s) 516 are shown as being part of system 510 and as being connected to server 512 by wired connection 514. It should be appreciated that all embodiments are not limited in this respect. For example, in other embodiments, storage device(s) 516 may be connected to server 512 using any suitable type of connection or communication medium, and may be internal or external to system 510. When storage device(s) 516 are external to system 510, the system may be communicatively coupled to storage device(s) 516 to obtain information from them in any suitable manner.

While FIG. 5 shows only a single healthcare provider using a single device 504, it should be recognized that embodiments of the present method are not limited in this respect and that system 510 may be configured to service any number of healthcare providers (e.g., hundreds, thousands, or greater) who may be using any number of devices (e.g., hundreds, thousands, or greater). Data associated with one or more patients made by each healthcare provider may be stored on at least one storage device (e.g., storage device 516 and/or on devices that the healthcare provider(s) use).

Regardless of where data associated with one or more patients involving one or more healthcare providers may be stored, such data may be stored in any suitable form. FIG. 6 shows a non-limiting example of a data structure 600 that may be used to store data associated with one or more patients in accordance with one embodiment. While in the illustrated embodiment data structure 600 is shown in the form of a table, this is not a limitation of the present method, as any suitable data structure may be used to store the data.

Data structure 600 may store any suitable data associated with one or more patients between any of one or more healthcare providers and system 510. In one non-limiting example described herein, data structure 600 may store patient identification data 602, patient data 604, library data 606, and/or data matching 608. In some embodiments, patient identification data 602 comprises information relating to patient identification such as name and date of birth. In some embodiments, patient data 604 comprises information relating to a patient's cancer type, gene fusion information, and/or HLA allele information. In some embodiments, library data 606 comprises information relating to peptide sequence, peptide-HLA affinity, sequences of DNA and/or RNA encoding peptides, gene fusion sequences, gene fusion cancer types, and IC₅₀. In some embodiments, data matching 608 comprises information relating to peptide population coverage, allele coverage, and information matching peptides to HLA alleles, peptides to gene fusions, and/or peptides to cancer types. However, it should be recognized that these examples are not limiting, and that data structure 600 may store any other data associated with one or more patients.

For each patient, data structure 600 may store one or more data records. A data record may store any suitable data associated with a patient and may store such data in any suitable format (e.g., in one or more fields). Each field may store any suitable amount of data and any suitable type of data and, for example, may store alphanumeric data representing the data directly, or a pointer to another location where data may be stored. In some instances, data structure 600 may store the same type of data record for each patient, but this is not a limitation on the data structure or other aspects of the methods described herein, as in other embodiments, data structure 600 may store one type of data record for one patient and another type of data record for another patient. For example, a data record for one patient may store a different amount of data than another data record for another patient.

Data structure 600 may store any suitable number of data records. In FIG. 6, data structure 600 is shown as storing four data records, but it should be appreciated that the data structure may store many more (e.g., hundreds, thousands, millions, etc.) data records.

Each data record in data structure 600 is shown as having four fields; however, this is for purposes of illustration only and is not a limitation of the present methods as any suitable number of fields may be used. For instance, any suitable number of fields may be used to store information identifying the patient, and any suitable number of fields may be used to store data associated with the patient.

FIG. 7 shows a flow chart of an illustrative process for matching patient data and library data, in accordance with some embodiments of the present method.

Process 700 begins in act 702, where patient data may be received from a healthcare provider. The patient data may be received by a system, such as system 510, and may be received in any suitable way. Next, process 700 proceeds to act 704, where library information is obtained.

After the library information is obtained in act 704, process 700 proceeds to decision block 706, where it is determined whether patient information obtained in act 702 matches library information obtained in act 704. For example, it may be determined, in decision block 706, whether the patient is a candidate for treatment with one or more peptide vaccines from the library. As disclosed herein, such data may include patient allele data, peptide sequence information, and/or any of the other types of data described herein.

If it is determined, in decision block 706, that library data does not match data associated with one or more patients, process 700 proceeds to act 712, where a patient may be identified as a candidate for de novo vaccine generation and treatment or a candidate for alternative treatment.

If it is determined in decision block 706 that library data matches patient data, process 700 proceeds to act 708, where at least a portion of the library data may be retrieved. The data to retrieve may be any suitable data and may be determined in any suitable way. After peptide library data associated with one or more patients is retrieved in act 708, process 700 proceeds to act 710, where peptide information is sent to the healthcare provider.

An illustrative implementation of a computer system 810 that may be used in connection with any of the embodiments of the method described herein is shown in FIG. 8. The computer system 800 may include one or more processors 810 and one or more articles of manufacture that comprise non-transitory computer-readable storage media (e.g., memory 820 and one or more non-volatile storage media 830). Processor 810 may control writing data to and reading data from memory 820 and non-volatile storage device 830 in any suitable manner, as the aspects of the method described herein are not limited in this respect.

To perform any of the functionality described herein, processor 810 may execute one or more processor-executable instructions stored in one or more non-transitory computer-readable storage media (e.g., memory 820), which may serve as non-transitory computer-readable storage media storing processor-executable instructions for execution by processor 810.

The terms “program” or “software” are used herein in a generic sense to refer to any type of computer code or set of processor-executable instructions that can be employed to program a computer or other processor to implement various aspects of embodiments as discussed herein. Additionally, it should be appreciated that according to one aspect, one or more computer programs that when executed perform methods described herein need not reside on a single computer or processor, but may be distributed in a modular fashion among different computers or processors to implement various aspects of the present method.

Programs for Fusion Detection in RNA Sequence and/or WGS Data

In some embodiments, any one of the more than 30 publicly available programs for fusion detection can be used (programs available at omicstools (omictools.com/gene-fusion-detection-category). In some embodiments, more than one program for fusion detection is used. In some embodiments, the results from different fusion detection programs may significantly diverge.

In some embodiments, fusion detection programs are alignment-based programs that map reads to a reference and infer breakpoint positions from discordantly aligned reads. The majority of existing programs are alignment-based programs. However, alignment-based programs may differ in references (genome, transcriptome or both) or aligners, e.g., STAR (ncbi.nlm.nih.gov/pmc/articles/PMC3530905/), TopHat2 (ncbi.nlm.nih.gov/pmc/articles/PMC4053844/) or bowtie2 (ncbi.nlm.nih.gov/pmc/articles/PMC3322381/) and therefore give very diverse results.

In some embodiments, de novo assembly-based programs perform transcriptome assembly and align obtained sequences to a reference transcriptome and thus find chimeric transcripts. In some embodiments, the de novo assembly-based program JAFFA (genomemedicine.biomedcentral.com/articles/10.1186/s13073-015-0167-x) can be used in ‘assembly’ mode.

In some embodiments, fusion detection programs are a hybrid of alignment-based and de-novo assembly-based approaches. In some embodiments, the hybrid approach first aligns reads to known transcriptome similar to the alignment-based approach. In some embodiments, the hybrid approach re-assembles unaligned reads and fragments spanning a breakpoint to new sequences. In some embodiments, the hybrid approach re-assembles unaligned reads and fragments spanning a breakpoint to new sequences using TRUP (ncbi.nlm.nih.gov/pmc/articles/PMC4300615/).

In some embodiments, fusion callers may be used for de novo assembly. In some embodiments, fusion callers consume a lot of resources and time. In some embodiments, fusion callers and alignment-based tools gave the same results.

In some embodiments, a program has filters that influence the results produced by the program. In some embodiments, a program has its own set of filters with specific default values. In some embodiments, a program has a filter for low fusion coverage that filters out low frequency junction or spanning reads. In some embodiments, a program has a filter for homology that filters out fusion partners with long homological regions. In some embodiments, a program has a filter for minimal distance between fusion partners that filters out potential read through transcripts. In some embodiments, a program has a promiscuity filter that filters out fusions containing partner transcripts which are presented in many other fusions. In some embodiments, a program generates a program-specific list of frequent false-positives.

In some embodiments, multiple fusion detection programs are used to determine a gene fusion recurrence rate. In some embodiments, four fusion detection programs are used to identify gene fusions. In some embodiments, a gene fusion is detected by two out of four fusion detection programs. In some embodiments, the fusion detection programs used are ChimeraScan (ncbi.nlm.nih.gov/pmc/articles/PMC3187648/), SOAP-fuse (ncbi.nlm.nih.gov/pmc/articles/PMC4054009/), and Integrate (genome.cshlp.org/content/early/2015/11/10/gr.186114.114.abstract).

Algorithm for Calculating Fusion-Derived Peptide Lengths

In some embodiments, fusion-derived peptide lengths are calculated from gene fusions. In some embodiments, computational algorithm (1) is used for calculating fusion-derived peptide lengths,

$\begin{matrix} {{S\left( {X,L} \right)} = {{Right}\left( {{SA}_{1},{{3 \cdot \left( {L - 1} \right)} + {{RF}\left( {{Right}\left( {{SA}_{1},1} \right)} \right)}\bigcap{{Left}\left( {{SB}_{2},{BT}} \right)}},{{BT} = {\begin{matrix} {{{RF}\left( {{Right}\left( {{SA}_{1},1} \right)} \right)} = \left. {{RF}\left( {{Left}\left( {{SB}_{2},1} \right)} \right)}\rightarrow{{3 \cdot \left( {L - 1} \right)} +} \right.} \\ {3 - {{RF}\left( {{Left}\left( {{SB}_{2},1} \right)} \right)}} \\ \left. {{{RF}\left( {{Right}\left( {{SA}_{1},1} \right)} \right)} \neq {{RF}\left( {{Left}\left( {{SB}_{2},1} \right)} \right)}}\rightarrow{3 -} \right. \\ {{{RF}\left( {{Right}\left( {{SA}_{1},1} \right)} \right)},{+ {{LRF}\left( {{Shift}\left( {{SB}_{2},{3 - {{RF}\left( {{Right}\left( {{SA}_{1},1} \right)} \right)}}} \right)} \right)}}} \end{matrix}}}} \right.}} & (1) \end{matrix}$

wherein X is a fusion of genes A and B, SA₁ is a transcript sequence of A to the left of the fusion breakpoint, SA₂ is a transcript sequence of A to the right of the fusion breakpoint, SB₁ is a transcript sequences of B to the left of the fusion breakpoint, SB₂ is a transcript sequence of B to the right of the fusion breakpoint, SA₁∩SB₂ is a fusion transcript sequence, SA₁∩SA₂ is a transcript sequence of gene A, SB₁∩SB₂ is a transcript sequence of gene B, L is the peptide length, Right and Left return a given number of bases to rightmost or leftmost, Shift skips a given number of bases on the left, RF is a position of a base in open reading frame, and LRF is the length of ORF. Fusion X yields a joint set of mutant peptides {S(X,L_(i))} where peptide length L_(i) varies in some predefined range L_(min) . . . L_(max).

Algorithm for HLA Genotyping

In some embodiments, HLA genotyping is calculated in silico from genome, exome, transcriptome, and/or HLA sequencing data. In some embodiments, a set of predicted HLA alleles that a patient may have is generated using computation algorithm (2),

$\begin{matrix} {{{CA}_{k} \in {CA}},{{\sum_{i}{CA}_{k}} \in {A_{ij} \geq \frac{H}{2}}}} & (2) \end{matrix}$

wherein H_(i) is a HLA genotyping algorithm, A_(ij) is a set of HLA alleles predicted by algorithm H_(i), and CA is a set of HLA alleles. In some embodiments, A_(ij) should have 4-digit precision (e.g., HLA-A0201). In some embodiments, the set of HLA alleles CA is used for matching patient and vaccine.

Algorithms for Predicting MHC-Peptide Binding

Algorithms are available for predicting MHC-peptide binding affinity and (algorithms available at cancerimmunity.org/resources/webtools/or cbs.dtu.dk/services/). In some embodiments, MHC-peptide binding was predicted with NetMHC and NetMHCpan programs (NetMHC (ncbi.nlm.nih.gov/pubmed/26258412, NetMHCpan ncbi.nlm.nih.gov/pubmed/25588790).

In some embodiments, MHC molecules of class I consist of a heavy chain and a light chain and bind to peptides comprising 8 to 11 amino acids. In some embodiments, MHC molecule of class I bind to peptides comprising 9 or 10 amino acids. In some embodiments, long peptides or entire proteins are degraded in the cell, bound to MHC proteins, and presented to cytotoxic T-cells.

In some embodiments, HLA proteins bind peptides comprising 8 to 14 amino acids. In some embodiments, peptides with predicted IC₅₀<500 nM are considered to bind to HLA proteins. In some embodiments, peptides with predicted IC₅₀<50 nM are considered as strong binders to HLA proteins. In some embodiments, peptides with predicted IC₅₀>500 nM are considered as non-binders to HLA proteins. In some embodiments, non-binding peptides are filtered out from a list of peptides. In some embodiments, a population coverage for each long peptide is calculated using only those HLA proteins that can bind its short derivatives. In some embodiments, a long peptide comprising 30 amino acids can be shortened into peptides comprising 9 amino acids for predicting binding to HLA proteins. In some embodiments, mutant peptides are compared to wild type counterparts for binding affinity.

Algorithm for Calculating Population Coverage of Fusion-Derived Peptides

In some embodiments, a population coverage of fusion-derived peptides is calculated. In some embodiments, a population coverage of fusion-derived peptides is an estimate of how many patients will be eligible candidates for vaccination with the fusion-derived peptide. In some embodiments, a population coverage of fusion-derived peptides is calculated from the incidence of the corresponding gene fusion. In some embodiments, a population coverage of fusion-derived peptides is calculated from the allele frequency of HLA proteins that bind to the fusion-derived peptide. In some embodiments, a population coverage of fusion-derived peptides is calculated using computation algorithm (3),

P=Σ _(i) Q(F _(i))(1−Σ_(j′)(1−Q(A _(ij′)))²  (3)

wherein A_(ij)′=∪_(k) (A_(jjk)), A_(ij′) is a set of alleles matching peptides yielded by fusion F_(i), F_(i) is a set of fusions yielding a set of peptides D_(ij) comprising the given peptide vaccine, A_(ijk) is the HLA alleles that can bind peptide D_(ij), Q(A_(ijk)) is the allele frequency of allele A_(ijk), Q(F_(i)) is the incidence rate of fusion F_(i), and P is the probability that a patient will be a candidate for treatment with the peptide vaccine.

Definitions

“Fusion transcript” refers to a product of fusion gene. Fusion transcript and chimeric transcript are used interchangeably.

“Fusion protein” or “chimeric protein” refers to a product of a fusion transcript and may emerge from genomic rearrangement, read through transcript, or trans-splicing. Fusion protein and chimeric protein are used interchangeably.

“Fusion variant” refers to a variant at particular breakpoints in fusion partner genes. “Fusion exonic variant” refers to a variant at breakpoints leading to fusion of the same partner gene exons.

“Point of junction” and “breakpoint” refer to the point at which two genes, transcripts, or proteins are fused together.

“Administering” or “administration” means providing a material to a subject in a manner that is pharmacologically useful.

“At risk” patients are patients that a health practitioner believes has a chance of having a disease, disorder or condition as provided herein.

“HLA proteins” refers to human leukocyte antigen (HLA) proteins that bind peptides resulting from proteolytic cleavage of protein antigens and representing potential T-cell epitopes, transporting them to the cell surface and presenting them there to specific cells, in particular cytotoxic T-lymphocytes or T-helper cells. HLA proteins are products of HLA genes that are classified into two gene groups coding for different proteins, namely proteins of HLA class I and proteins of HLA class II. HLA class I proteins and HLA class II proteins are specialized for different antigen sources. HLA class I proteins present endogenously synthesized antigens, for example viral proteins and tumor antigens. HLA class II proteins present protein antigens originating from exogenous sources, for example bacterial products. “HLA protein” and “MHC protein” are used interchangeably.

“Vaccine” refers to a composition for generating immunity for the prophylaxis and/or treatment of diseases. Vaccines are compositions comprising antigens and are intended to be used in humans or animals for generating specific defense and protective substance by vaccination.

“Peptide” refers to a series of residues, typically L-amino acids, connected one to the other, typically by peptide bonds between the α—amino and carboxyl groups of adjacent amino acids. Peptides can be a variety of lengths, either in neutral (uncharged) forms or in forms which are salts, and either free of modifications or containing modifications, subject to the condition that the modification not destroy the biological activity of the peptide as described herein. It should be appreciated that a “peptide sequence” or “sequence” may be used to refer to a “peptide” having a particular sequence in the present disclosure in some contexts. In some embodiments, a “long peptide” refers to a peptide comprising about 11-30 amino acid residues corresponding to the fusion breakpoint. In some embodiments, the long peptide is processed into a neoantigenic peptide comprising about 8-11 amino acid residues.

“Neoantigen” refers to a tumor antigen which is produced from tumor-specific mutations in expressed genes. “Fusion-derived”, “fusion-specific”, and “neoantigen” are used interchangeably. “Neoantigenic peptides” refers to peptides that comprise tumor-specific amino acid sequences (e.g., that contain a fusion junction that is only found in cancer cells due to the genetic rearrangement that is only present in the cancer cells). “Fusion-derived peptide”, “fusion-specific peptide”, and “neoantigenic peptide” are used interchangeably.

“IC₅₀” refers to the concentration of gene fusion peptide necessary for inhibiting binding of a standard peptide to the HLA protein by fifty percent.

“Patient coverage” refers to the percentage of patients (e.g., in a population, for example in a population that is being treated or evaluated) that have a gene fusion corresponding to a fusion-specific neoantigen present in the vaccine library and that have HLA proteins capable of binding the fusion-specific neoantigen.

“Pulsing” refers to the process of antigen loading onto a cell, wherein the antigen may be a nucleic acid or a peptide.

EXAMPLES Example 1: Therapeutic Cancer Vaccines Comprising Fusion-Specific Peptides

A therapeutic cancer vaccine should guide the immune response and be readily combine with other therapies. Therapeutic cancer vaccines can be composed of processed tumor cells, peptides, whole proteins, DNA, or mRNA. Vaccine antigens include tumor-associated antigens (TAA), differentiation antigens, or cancer-testis antigens. However, many antigens that are present in cancer cells are also present in peripheral organs, thus specifically targeting cancer cells is difficult. The first and only FDA approved therapeutic cancer vaccine called “Provenge” showed modest efficacy in prostate cancer (ncbi.nlm.nih.gov/pubmed/16809734).

Advances in sequencing technologies and bioinformatics algorithms have made it possible to identify mutations in whole cancer genomes. However, “de novo” identification of mutations from whole genome (WGS), whole exome (WES) or RNA sequencing data is expensive and time consuming. Many patients are in need of immediate treatment, especially patients with aggressive tumors like lung cancer, advanced melanoma, or acute leukemia.

Fusion genes have a higher reoccurrence rate than the reoccurrence rates of missense mutations or frameshift mutations. Highly mutated genes including TP53, PIK3CA, EGFR, KRAS, BRAF, and NRAS can be found across different tumor types, yet the reoccurrence rate of mutations in these genes is low. Moreover, recurrent fusion genes and recurrent driver mutations are often mutually exclusive. Thus, recurrent fusions are attractive as a source of neoantigens for the construction of “off-the-shelf” vaccine libraries for at least two reasons: high recurrence rate and the ability to drive cancer (ncbi.nlm.nih.gov/pubmed/25500544). The following examples provide a background for the construction and methods of use of a therapeutic cancer vaccine library comprising fusion-specific vaccines.

Murine Neoantigen Peptide Vaccines

In one study (ncbi.nlm.nih.gov/pubmed/25428507), neoantigenic peptides were identified and used for vaccination of mice. The study showed that two 3-methylcholanthrene-induced sarcoma cell lines d42m1-T3 and F244 were effectively rejected with anti-PD-1 and/or anti-CTLA-4 therapies. The immunological nature of the rejection was confirmed with multiple experimental approaches including depleting CD4+ and CD8+ T-cells with mouse antibodies, performing experiments in mice lacking T, B, natural killer T-cells or dendritic cells, and generating immunological memory in the mice.

The study identified neoantigens responsible for the checkpoint blockade therapy-mediated tumor rejection using a genomic approach. The approach was initially established for identifying TSA responsible for spontaneous rejection of d42m1 sarcomas (ncbi.nlm.nih.gov/pubmed/22318521). The study included features including mutation calling from exome sequencing data, translating mutations to corresponding protein sequences, predicting peptide-MHC class I binding affinity for each epitope, prioritizing epitopes, and filtering out epitopes with lower expression level and lower binding affinity in comparison to the wild-type peptides. Two mutant epitopes for murine MHC H-2 Kb were identified in this study: ITYTWTRL (SEQ ID NO: 612) (A506T mutation in alpha-1,3-glucosyltransferase) and VGFNFRTL (SEQ ID NO: 613) (G1254V mutation in laminin alpha subunit 4). Both epitopes were shown to be targets of CD8+ T-cells generated as a consequence of anti-PD1 treatment by experiments including MHC tetramer-binding assays, mass spectrometry detection of epitopes, and ELISPOT assays. Mice were vaccinated with two peptide vaccines based on the identified mutant epitopes and 9/10 mice rejected their tumors and survived. As a negative control, mice were vaccinated with human papillomavirus 28-mer peptides and only 1/10 mice survived. In multiple experiments of mice vaccination, the survival rate for mice vaccinated with therapeutic neoantigenic vaccines was 85% while the survival rate of mice vaccinated with human papillomavirus peptides was only 10%.

In another study (ncbi.nlm.nih.gov/pubmed/25901682), a bioinformatics approach was used to detect tumor-specific mutations from cancer exome sequencing data for B 16F10 tumor (melanoma) and colon carcinoma model CT26 in three independent mouse models with different MHC backgrounds. Mutant epitopes were prioritized using both MHC class I and class II prediction algorithms. A considerable fraction of detected mutations produced immunogenic neoantigens which can be recognized by both CD8+ and CD4+ T-cells. Vaccination with the identified immunogenic neoantigens produced anti-tumor activity and complete tumor rejection. About two-thirds of the mice vaccinated with the neoantigenic peptides were alive at day 100 while all untreated mice died at day 65. Interestingly, depletion experiments showed that CD4+ instead of CD8+ T-cells played a major role in anti-cancer response efficacy. Also, immunization with neoantigens encoded by mRNA elicited higher anti-tumor activity than immunization with peptides only. Taken together, this study showed that both MHC class I and class II restricted epitopes can be selected based on binding affinity and can display high anti-tumor potency.

In another study (ncbi.nlm.nih.gov/pubmed/25428506), neoepitopes were identified using whole-exome and transcriptome sequencing analysis with mass spectrometry. This approach identified neoepitopes in MC-38 and TRAMP-C1 mouse tumor cell lines using mutation calling from sequencing data, identification of expressed neoantigens using RNA-sequencing data, prediction of MHC class I binding interactions, and filtering of immunogenic epitopes. Six epitopes were predicted to bind with an IC₅₀ less than 500 nM. Immunization of C57BL/6 mice with peptides encoding all six mutated epitopes elicited CD8+ T-cell responses in three out of six mice. Vaccination with long peptides encoding mutant epitopes had therapeutic and preventive effects. Subsequent challenging of vaccinated mice with MC-38 tumor cells didn't result in tumor spreading or growth compared to mice immunized with adjuvant only which experienced tumor spreading and growth.

As described herein, bioinformatics pipelines for detecting and prioritizing neoantigens in whole cancer exomes and/or transcriptomes have made it possible to select targets for vaccination using solely in silico simulation steps. Computational pipelines validated in mice models have improved mouse survival rates and inspired confidence in the potential success of vaccination with personalized neoantigenic vaccines in humans.

Average Bioinformatics Pipelines for Neoantigen Prediction

The following two examples illustrate a non-limiting schematic pipeline used for neoantigen generation from sequencing data (FIG. 1).

In one study (ncbi.nlm.nih.gov/pubmed/24894089), epitope-MHC class I binding prediction algorithms were applied to a large set of neoantigens which had been known to induce strong anti-tumor activity or long-term cancer control. The study analyzed 40 epitopes previously identified as cytotoxic T-cell targets in the literature including 35 epitopes resulting from missense mutations and 5 epitopes resulting from frame-shift mutations. All epitopes were restricted by HLA class I alleles and were present in non-small cell lung cancer, melanoma, renal cell carcinoma, bladder cancer, B-cell acute lymphoblastic leukemia, multiple myeloma, and chronic lymphocytic leukemia. All epitopes were neoantigens that had been identified from cloning, mass spectrometry experiments, genomic mutations, and epitope-binding predictions. Using artificial neural network based prediction algorithms, 27 of 31 of the epitopes recognized by T-cells were predicted to have binding affinity of less than 500 nM to MHC class I proteins. Two-thirds of the patients experienced spontaneous complete tumor regression or tumor regression following therapy. Thus, in silico peptide-MHC class I binding predictions provided a reliable tool to identify neoantigens from exome and/or transcriptome data, and inclusion of such neoantigens in vaccine formulations provided tumor regression in patients.

In another study (ncbi.nlm.nih.gov/pubmed/24891321), neoantigens in human cancer genomes were identified using bioinformatics. A bioinformatics pipeline was applied to 91 whole exomes obtained from chronic lymphocytic leukemias (CLL) biopsies from a group of patients who developed durable remission after allo-HSCT. On average 20 neoantigens derived from 16 missense mutations were predicted to bind HLA class I proteins and more than 50% of all neoantigen were confirmed to bind HLA proteins with biochemical studies. The general steps of the computational pipeline were DNA sequencing, mutation calling, peptide-MHC class I predictions, and experimental validation of binding peptides. From a total of 1838 detected mutations, 3 general classes of mutations were identified including missense, frameshift and splice site mutations. The most abundant class of mutations were missense mutations which represented more than 90% of all detected mutations in cancer genomes (or exomes). A computational pipeline was applied to 2488 whole exome sequences from 13 tumor types and to a large set of HLA alleles. The analysis revealed that one point mutation produced on average 1 to 5 neoantigens and 1 frameshift mutation produced 4 neoantigens with an IC₅₀<50 nM. Neoantigens derived from frameshift mutations and gene fusions are expected to be more specific and more immunogenic because there is no corresponding wild type peptide. The study demonstrated that neoantigens derived from frameshift mutations and from gene fusions can be predicted using computational methods.

Vaccines Comprising Modified Fusion-Derived Peptides

The Wilms tumor gene 1 (WT1) can be used as a biomarker in different cancer types including acute myeloid leukemia (AML). In the clinical trial NCT00398138, WT1-positive patients with AML were treated with synthetic analogs of WT1 protein fragments in combination with adjuvants. Synthetic peptide analogs of WT1 protein fragments were designed to bind HLA molecules better than wild-type counterparts and were shown to more effectively induce a WT1-specific T-cell response compared to wild-type counterparts.

Anchor-modified peptides derived from PASD1 were shown to induce a cytotoxic T-cell response against tumor cells in AML patients. Interestingly, their non-modified wild-type analogs demonstrated no detectable binding to HLA proteins. These two examples demonstrate that neoantigenic peptide modifications can lead to an increase in peptide immunogenicity.

Vaccines Based on Fusion-Derived Neoantigens

The Philadelphia chromosome is the result of a translocation between chromosomes 22 and 9. This translocation is present in several cancers types and most notably the translocation is present in ˜95% of chronic myelogenous leukemia (CML) cases. The translocation produces a fusion between BCR and ABL1 genes. The ABL1 kinase is constitutively active in the BCR/ABL1 fusion protein and this upregulation of activity leads to dysregulation of cell division and development of cancer.

The sequence spanning the BCR/ABL1 breakpoint is absent in normal tissues and is present only in cancer cells, thus it may be recognized and attacked by the immune system. In a series of recent studies, peptides spanning the BCR/ABL breakpoint were shown to stimulate the immune response.

Cancer specific gene fusions have been used as neoantigens in several anti-cancer vaccines (Table 1). The EWS/FLI1 gene fusion is present in more than 85% of Ewing's sarcoma tumors (ncbi.nlm.nih.gov/pubmed/17250957) and the PAX-3/FKHR gene fusion is present in 55% of patients with alveolar rhabdomyosarcoma (ARMS) (ncbi.nlm.nih.gov/pubmed/12039929).

TABLE 1 List of fusions used as neoantigens in anti-cancer vaccines. Gene Fusion Patent BCR/ABL-1 [1-5] google.com.ar/patents/U.S. Pat. No. 5,997,869 EWS/FLI-1 (ncbi.nlm.nih.gov/pubmed/12039929) google.com.ar/patents/U.S. Pat. No. 5,997,869 PAX-3/FKHR (ncbi.nlm.nih.gov/pubmed/12039929) google.com.ar/patents/U.S. Pat. No. 5,997,869 TMPRSS2/ERG (ncbi.nlm.nih.gov/pubmed/24149465)

Example 2: Follicular Lymphoma (FL) Gene Fusions are Present in Multiple Cancer Types

Detection of recurrent chimeric transcripts was performed on 34 follicular lymphoma (FL) transcriptome samples from SRP048820 (ncbi.nlm.nih.gov/pubmed/25607463) and SRP056293 (ncbi.nlm.nih.gov/pmc/articles/PMC4676270/). Transcriptome samples included read through transcripts, products of trans-splicing, and chimeric transcripts formed as a result of genomic rearrangements. Chimeric transcripts were identified as recurrent if present in one or more of the FL transcriptome samples. Chimeric transcripts were identified as present in the sample if detected using two or more software programs, wherein the software programs were ChimeraScan, SOAPFuse, and Integrate.

An average of 28-29 fusion candidates were detected per sample. A total of 308 fusion candidates were detected with 149 of the fusion candidates found in more than one sample. A number of gene fusions present in the FL samples are also found in other cancer types including gastric, colon, breast, and prostate cancers (Table 2).

Neoantigenic peptides for each recurrent fusion protein having a predicted IC50 less than 500 nM to HLA class I proteins were selected. The prediction analysis can be performed using various length peptides, for example a peptide with 9 amino acids corresponding to 9 amino acids of the fusion junction. HLA class I alleles that bind to peptides with an IC₅₀ less than 500 nM are identified as binding (Table 3). All fusion-derived peptides were novel and could be placed into a vaccine library. Patients are eligible for vaccination if they have a gene fusion corresponding to a fusion-derived peptide in the library and if the patient has at least one MHC class I alleles capable of binding to the fusion-derived peptide in the library. Methods of selecting a patient for vaccination and vaccine compositions are described herein.

TABLE 2 Recurrent Fusions Detected in Follicular Lymphoma (FL) Samples Breakpoint Number of Samples Non-FL Cancer Type Gene Fusion Coordinates Fusion/Total (References) DUS4L/BCAP29 chr7: 107217037 4/34 Gastric Cancer chr7: 107221204 (ncbi.nlm.nih.gov/pubmed/24240688) RRM2/C2orf48 chr2: 10269281 2/34 BT474 and SKBR3 cell lines chr2: 10281981 (ncbi.nlm.nih.gov/pubmed/23956304) PRKAA1/TTC33 chr5: 40764616 13/34  Colon, Kidney, Stomach, Breast, chr5: 40747121 Ovary, Uterus Cancers (ncbi.nlm.nih.gov/pubmed/23226102) MTG1/LOC619207 chr10: 135216277 8/34 Breast Cancer chr10: 135269741 (ncbi.nlm.nih.gov/pubmed/22496456) CIRBP/C19orf24 chr19: 1274439 14/34  Prostate Cancer chr19: 1277182 (google.com/patents/WO2012149522A1?cl=en)

TABLE 3 Predicted HLA Alleles of Recurrent Fusion-Derived Peptides. Gene Number of HLA class I alleles Fusion Fusion Sequence peptides (9 AA) (IC50 < 500 nM) DUS4L/ VWRITGTDGVKKKMTLQW  13 HLA-A*02:01, HLA-A*02:02, HLA-A*02:03, HLA-A*02:06, BCAP29 AAV HLA-A*02:11, HLA-A*02:12, HLA-A*02:16, HLA-A*02:19, (SEQ ID NO.: 404) HLA-A*02:50, HLA-A*11:01, HLA-B*15:03, HLA-B*27:20, HLA-B*39:01 RRM2/ RLMLELGFSKVLGDREVQS  37 HLA-A*02:01, HLA-A*02:02, HLA-A*02:03, C2orf48 RWSPGPRGDSTPVREMETN HLA-A*02:06, HLA-A*02:11, HLA-A*02:12, HPPSVRG HLA-A*02:16, HLA-A*02:19, HLA-A*02:50, (SEQ ID NO.: 405) HLA-A*30:01, HLA-A*31:01, HLA-A*32:07, HLA-A*33:01, HLA-A*68:01, HLA-B*07:02, HLA-B*15:03, HLA-B*18:01, HLA-B*27:20, HLA-B*40:01, HLA-B*40:02, HLA-B*40:13, HLA-B*42:01, HLA-B*44:02, HLA-B*45:01, HLA-B*73:01, HLA-C*03:03, HLA-C*07:01, HLA-C*12:03 PRKAA1/ TYLLDFRSIDEWLPLGGRG  34 HLA-A*02:03, HLA-A*02:06, HLA-A*02:11, TTC33 KLVRRSQRSLPSSLKLKLLM HLA-A*02:16, HLA-A*02:50, HLA-A*03:01, RRM HLA-A*11:01, HLA-A*30:01, HLA-A*31:01, (SEQ ID NO.: 406) HLA-A*32:07, HLA-A*32:15, HLA-A*33:01, HLA-A*68:23, HLA-B*07:02, HLA-B*08:01, HLA-B*15:01, HLA-B*15:03, HLA-B*15:17, HLA-B*27:05, HLA-B*27:20, HLA-B*35:01, HLA-B*39:01, HLA-B*40:13, HLA-B*42:01, HLA-B*53:01, HLA-B*57:01, HLA-B*58:01 HLA-C*03:03, HLA-C*12:03,HLA-C*15:02 MTG1/ LYTLNKHQRFGWTRCSEAG 208 HLA-A*31:01, HLA-B*27:20, HLA-C*06:02 LOC619207 VQTQHVRRSGVGPTPRGM GIRVQPGVDAGRGLCRVQA AGLRPCRGRPQVCPAAWR DGPALASQRVLPGQRVLPL GVQPWLMVPEPVPPRMGG GRAVLQRHFPGAPAGEGPQ SLRGTPRDQKREWGGPPLC PACGGGHGVLPGAGVRPCA PGPPPGRGRRQEVPGLQGY RAHHPQLQTGQQLPQRLRP AAGRRGGLLR (SEQ ID NO.: 407) CIRBP/ non-coding   0 — C19orf24

Example 3: Fusion-Derived Peptides Having High Percentages of Patient Population Coverage

Two fusion transcripts can be found in solitary fibrous tumors. The transcripts are formed from fusion of exon 4 of the Nab2 gene (5′ partner gene) with exon 2 of the Stat6 gene (3′ partner gene) and exon 6 of the Nab2 gene (5′ partner gene) with exon 16 of the Stat6 gene (3′ partner gene). The amino acid sequence of the Nab2/Stat6 fusion protein is shown below. A novel amino acid sequence is generated when exon 4 of Nab2 is fused with exon 2 of Stat6 because of the presence of an untranslated region at the beginning of exon 2 of Stat6. Exon 6 of the Nab2 gene is fused with exon 16 of the Stat6 gene in frame.

Nab2/Stat6 (Nab2 exon 4 to Stat6 exon 2) fusion protein (COSF1547) (SEQ ID NO.: 408) MHRAPSPTAEQPPGGGDSARRTLQPRLKPSARAMALPRTLGELQLYRVLQ RANLLSYYETFIQQGGDDVQQLCEAGEEEFLEIMALVGMATKPLHVRRLQ KALREWATNPGLFSQPVPAVPVSSIPLFKISETAGTRKGSMSNGHGSPGE KAGSARSFSPKSPLELGEKLSPLPGGPGAGDPRIWPGRSTPESDVGAGGE EEAGSPPFSPPAGGGVPEGTGAGGLAAGGTGGGPDRLEPEMVRMVVESVE RIFRSFPRGDAGEVTSLLKLNKKLARSVGHIFEMDDNDSQKEEEIRKYSI IYGRFDSKRREGKQLSLHELTINEAAAQFCMRDNTLLLRRVELFSLSRQV ARESTYLSSLKGSRLHPEELGGPPLKKLKQEATSKSQIMSLWGLVSKMPP EKVQRLYVDFPQHLRHLLGDWLESQPWEFLVGSDAFCCNLASALLSDTVQ HLQASVGEQGEGSTILQHISTLESIYQRDPLKLVATFRQILQGEKKAVME QFRHLPMPFHWKQEELKFKTGLRRLQHRVGEIHLLREALQKGAEAGQVSL HSLIETPANGTGPSEALAMLLQETTGELEAAKALVLKRIQIWKRQQQLAG NGAPFEESLAPLQERCESLVDIYSQLQQEVGAAGGELEPKTRASLTGRLD EVLRTLVTSCFLVEKQPPQVLKTQTKFQAGVRFLLGLRFLGAPAKPPLVR ADMVTEKQARELSVPQGPGAGAESTGEIINNTVPLENSIPGNCCSALFKN LLLKKIKRCERKGTESVTEEKCAVLFSASFTLGPGKLPIQLQALSLPLVV IVHGNQDNNAKATILWDNAFSEMDRVPFVVAERVPWEKMCETLNLKFMAE VGTNRGLLPEHFLFLAQKIFNDNSLSMEAFQHRSVSWSQFNKEILLGRGF TFWQWFDGVLDLTKRCLRSYWSDRLIIGFISKQYVTSLLLNEPDGTFLLR FSDSEIGGITIAHVIRGQDGSPQIENIQPFSAKDLSIRSLGDRIRDLAQL KNLYPKKPKDEAFRSHYKPEQMGKDGRGYVPATIKMTVERDQPLPTPELQ MPTMVPSYDLGMAPDSSMSMQLGPDMVPQVYPPHSHSIPPYQGLSPEESV NVLSAFQEPHLQMPPSLGQMSLPFDQPHPQGLLPCQPQEHAVSSPDPLLC SDVTMVEDSCLSQPVTAFPQGTWIGEDIFPPLLPPTEQDLTKLLLEGQGE SGGGSLGAQPLLQPSHYGQSGISMSHMDLRANPSW Nab2/Stat6 (Nab2 exon 6 to Stat6 exon 16) fusion protein (COSF1561) (SEQ ID NO.: 409) MHRAPSPTAEQPPGGGDSARRTLQPRLKPSARAMALPRTLGELQLYRVLQ RANLLSYYETFIQQGGDDVQQLCEAGEEEFLEIMALVGMATKPLHVRRLQ KALREWATNPGLFSQPVPAVPVSSIPLFKISETAGTRKGSMSNGHGSPGE KAGSARSFSPKSPLELGEKLSPLPGGPGAGDPRIWPGRSTPESDVGAGGE EEAGSPPFSPPAGGGVPEGTGAGGLAAGGTGGGPDRLEPEMVRMVVESVE RIFRSFPRGDAGEVTSLLKLNKKLARSVGHIFEMDDNDSQKEEEIRKYSI IYGRFDSKRREGKQLSLHELTINEAAAQFCMRDNTLLLRRVELFSLSRQV ARESTYLSSLKGSRLHPEELGGPPLKKLKQEVGEQSHPEIQQPPPGPESY VPPYRPSLEEDSASLSGESLDGHLQAVGSCPRLTPPPADLPLALPAHGLW SRHILQQTLMDEGLRLARLVSHDRVGRLSPCVPAKPPLAGSPQIENIQPF SAKDLSIRSLGDRIRDLAQLKNLYPKKPKDEAFRSHYKPEQMGKDGRGYV PATIKMTVERDQPLPTPELQMPTMVPSYDLGMAPDSSMSMQLGPDMVPQV YPPHSHSIPPYQGLSPEESVNVLSAFQEPHLQMPPSLGQMSLPFDQPHPQ GLLPCQPQEHAVSSPDPLLCSDVTMVEDSCLSQPVTAFPQGTWIGEDIFP PLLPPTEQDLTKLLLEGQGESGGGSLGAQPLLQPSHYGQSGISMSHMDLR ANPSW

In the case of COSF1547, a long peptide having a sequence GPPLKKLKQEATSKSQIMSLWGLVSKM (SEQ ID NO.: 410) was used for generating neoantigenic peptides (8-11 amino acids) for predicting peptide binding to MHC class I proteins. The example below contains predicted neoantigenic peptides having 9 amino acids.

In the case of COSF1561, a long peptide having a sequence PCVPAKPPLAGSPQIENIQP (SEQ ID NO: 614) was used for generating neoantigenic peptides having 8-11 amino acids for predicting peptide binding to MHC class I proteins.

A set of neoantigenic peptides comprising 8-11 amino acids was generated for all available MHC class I alleles using prediction algorithms described herein and filtering out of all epitopes with IC₅₀>500 nM. Those MHC class I proteins that are able to effectively bind Nab/Stat6 fusion-derived neoepitopes are listed in the Table 4.

For Nab2/Stat6 COSF1547, the allele coverage was calculated to be 94% meaning that 94% of the population can effectively present neoantigenic peptides derived from the long peptide spanning the Nab2/Stat6 fusion breakpoint. The Nab2/Stat6 COSF1547 fusion incidence rate is around 34% in solitary fibrous tumors. The patient coverage of the fusion-derived long peptide from Nab2/Stat6 COSF1547 is around 32%. For COSF1561, patient coverage of the fusion-derived long peptide is about 20%.

Both recurrent Nab2/Stat6 fusion-derived long peptides spanning fusion breakpoints are original and placed into the vaccine library. Results for another less frequent Nab2/Stat6 fusion (COSF1561, exon 6 of Nab2 to exon 17 of Stat6) are also shown in Table 4.

TABLE 4 Nab/Stat6 fusion-derived peptides predicted to bind HLA alleles. Long peptide spanning HLA class I alleles fusion breakpoint and  8-11-mer neoantigenic  that bind neoantigens Fusion yielding neoantigens peptides (SEQ ID NO.) (IC50 < 500 nM) Nab2/Stat6 GPPLKKLKQE ATSKSQI MS ATSKSQIM (429) HLA-A*02:01 COSF1547 LWGLVSKM EATSKSQI (430) HLA-A*02:02 (SEQ ID NO.: 426) IMSLWGLV (431) HLA-A*02:03 KSQIMSLW (432) HLA-A*02:06 QIMSLWGL (433) HLA-A*02:11 SKSQIMSL (434) HLA-A*02:17 EATSKSQIM (435) HLA-A*03:01 KLKQEATSK (436) HLA-A*11:01 QEATSKSQI (437) HLA-A*30:01 QIMSLWGLV (438) HLA-A*32:01 SQIMSLWGL (439) HLA-A*68:01 TSKSQIMSL (440) HLA-A*68:02 ATSKSQIMSL (441) HLA-A*69:01 IMSLWGLVSK (442) HLA-B*15:01 KKLKQEATSK (443) HLA-B*15:03 KQEATSKSQI (444) HLA-B*15:17 KSQIMSLWGL (445) HLA-B*35:01 QEATSKSQIM (446) HLA-B*39:01 SQIMSLWGLV (447) HLA-B*40:01 TSKSQIMSLW (448) HLA-B*40:02 ATSKSQIMSLW (449) HLA-B*44:02 EATSKSQIMSL (450) HLA-B*45:01 IMSLWGLVSKM (451) HLA-B*48:01 KQEATSKSQIM (452) HLA-B*57:01 KSQIMSLWGLV (453) HLA-B*58:01 LKQEATSKSQI (454) HLA-C*03:03 QEATSKSQIMS (455) HLA-C*12:03 QIMSLWGLVSK (456) HLA-C*15:02 SQIMSLWGLVS (457) Nab2/Stat6 PCVPAKPPLAGSPQIENIQP PLAGSPQI (458) HLA-A*02:11 COSF1561 (SEQ ID NO.: 427) PPLAGSPQI (459) HLA-B*07:02 KPPLAGSPQI (460) HLA-B*15:17 LAGSPQIENI (461) HLA-B*42:01 GSPQIENIQPF (462) HLA-C*03:03 PLAGSPQIENI (463) HLA-C*12:03 Nab2/Stat6 PCVPAKPPLAAEQMGKDG AEQMGKDG (464) HLA-A*03:01 COSF1561 RGY LAAEQMGK (465) HLA-A*68:01 (SEQ ID NO.: 428) PPLAAEQM (466) HLA-B*07:02 KPPLAAEQM (467) HLA-B*35:01 PLAAEQMGK (468) HLA-B*42:01 VPAKPPLAA (469) HLA-B*44:02 AEQMGKDGRGY (470) HLA-B*44:03 LAAEQMGKDGR (471) HLA-B*45:01 PAKPPLAAEQM (472) HLA-C*03:03 HLA-C*12:03

Example 4: Prostate Cancer Vaccine Compositions Comprising TMPRSS2/ERG Fusion Peptides

In total, 8 exonic variants of the TMPRSS2/ERG fusion from the COSMIC database were analyzed. The majority of the discovered antigenic peptides were not previously published. The TMPRSS2/ERG fusion is specific to prostate cancer and has quite a high incidence rate. The major protein coding exonic variant is estimated to be found in over 10% of cases. Further analysis showed that a vaccine based on TMPRSS2/ERG fusion-derived neoantigens can be used for about 20,000 prostate cancer patients a year in the USA.

TABLE 5 Population coverage of TMPRSS2/ERG fusion peptides. Long peptide spanning fusion breakpoint and Population yielding neoantigens HLA class (alleles that bind covered by (number of neoantigens) neoantigens (IC50 < 500 nM) the alleles DGVSHCPGGEDENRCGSLISCE (3) B*40:01, B*40:02, C*12:03 18% (SEQ ID NO.: 473) FLVGAALAAGLLWKFRSLISCE (13) A*02:01, A*02:02, A*02:03, A*02:06, A*02:11, 73% (SEQ ID NO.: 474) A*02:17, A*30:01, A*31:01,A*33:01, A*68:01, B*08:01, B*15:03, C*03:03, C*12:03 FLVGAALAAGLLWKFRTLLMNAVW A*02:01, A*02:02, A*02:03, A*02:06, A*02:11, 92% PKAGRW (22) A*02:17, A*03:01, A*11:01, A*24:03, A*30:01, (SEQ ID NO.: 475) A*31:01, A*32:01, A*33:01, A*68:01, A*69:01, B*08:01, B*15:03, B*15:17, B*27:05, B*39:01, B*57:01, B*58:01, C*03:03, C*12:03, C*14:02, C*15:02 MALNSEALSVVSEDQSLFEC (9) A*02:01, A*02:02, A*02:03, A*02:06, A*02:11, 67% (SEQ ID NO.: 476) A*02:17, A*68:02, A*69:01, B*15:03, B*15:17, B*35:01, B*40:02, B*45:01, B*53:01, C*03:03, C*12:03, C*14:02, C*15:02 MALNSPSGSEQLVDGLAY (11) A*01:01, A*02:02, A*02:11, A*02:17, A*26:01, 88% (SEQ ID NO.: 477) A*29:02, A*68:02, B*07:02, B*15:01, B*15:03, B*15:17, B*18:01, B*35:01, B*40:01, B*40:02, B*42:01, B*44:02, B*44:03, B*45:01, C*03:03, C*15:02 MALNSVIPGSLETRGKPC (10) A*02:01, A*02:02, A*02:03, A*02:06, A*02:11, 78% (SEQ ID NO.: 478) A*11:01, A*30:01, A*31:01, A*68:01, A*69:01, B*15:01, B*15:03, B*15:17, B*35:01, C*03:03, C*12:03, C*14:02 VCTQPKSPSGTVCTSRSLISCE (5) A*31:01, A*68:02, B*15:17, C*03:03 17% (SEQ ID NO.: 479) VCTQPKSPSGTVCTSSYSRIFGDPRK A*02:01, A*02:02, A*02:03, A*02:11, A*03:01, 98% AVLT (60) A*11:01, A*29:02, A*30:01, A*30:02, A*31:01, (SEQ ID NO.: 480) A*32:01, A*33:01, A*68:01, A*68:02, B*07:02, B*15:01, B*15:03, B*15:17, B*35:01, B*42:01, B*44:03, B*53:01, B*57:01, B*58:01, C*03:03, C*05:01, C*07:02, C*08:02, C*12:03, C*14:02, C*15:02

Example 5: Universal Cancer Vaccine Compositions Comprising ETV6/NTRK3 Fusion Peptides

Four exonic variants of the ETV6/NTRK3 fusion from the COSMIC database were analyzed to predict neoantigen peptides. All of the predicted neoantigen peptides were not previously published. According to the COSMIC database, this fusion was found in congenital (infantile) fibrosarcoma, mesoblastic nephroma, breast ductal secretory carcinoma, mammary analogue secretory carcinoma of salivary glands, thyroid carcinoma, and intestine carcinoma. This demonstrated that neoantigen vaccines based on a single fusion can target a wide spectrum of tumor types.

TABLE 6 ETV6/NTRK3 fusion-derived peptides predicted to bind HLA alleles. Long peptide spanning fusion breakpoint and Population yielding neoantigens HLA class I alleles that bind  covered by (number of neoantigens) neoantigens (IC50 < 500 nM) the alleles IHTQPEVILHQNHEEDVQH A*02:02, A*02:03, A*02:11, A*33:01, A*68:01, B*15:03, 68% IKRRDIVLKRE (8) B*40:01, B*44:02, C*06:02, C*07:01, C*12:03 (SEQ ID NO.: 481) IHTQPEVILHQNHEEGPVA A*02:02, A*02:03, A*02:11, A*02:17, B*15:03, B*15:09, 48% VISGEEDSASP (10) B*39:01, B*40:01, B*40:02, B*45:01, C*07:01, C*12:03, (SEQ ID NO.: 482) C*14:02 VSPPEEHAMPIGRIADVQH A*02:03, A*02:06, A*02:11, A*03:01, A*11:01, A*30:01, 92% IKRRDIVLKRE (14) A*31:01, A*33:01, A*68:01, A*68:02, B*07:02, B*08:01, (SEQ ID NO.: 483) B*27:05, B*35:01, B*42:01, B*58:01, C*03:03, C*06:02, C*07:01, C*12:03, C*15:02 VSPPEEHAMPIGRIADVQH A*02:02, A*02:03, A*02:06, A*02:11, A*02:17, A*30:01, 66% IKRRDIVLKRE (11) A*32:01, A*68:02, A*69:01, B*07:02, B*15:01, B*15:17, (SEQ ID NO.: 484) B*27:05, B*35:01, B*39:01, B*42:01, B*58:01, C*03:03, C*12:03, C*14:02, C*15:02

Example 6: Identification of Novel Peptides in Previously Studied Gene Fusion (FUS/ERG)

FUS/ERG fusion can be found, for example, in acute myeloid leukaemia and occurs due to fusion of exon 7 of the FUS gene with exon 11 of the ERG gene. The amino acid sequence of the FUS/ERG fusion protein is shown below.

FUS/ERG (Fus exon 7 to exon 11 of Erg) fusion protein (COSF315) (SEQ ID NO.: 485) MASNDYTQQATQSYGAYPTQPGQGYSQQSSQPYGQQSYSGYSQSTDTSGY GQSSYSSYGQSQNTGYGTQSTPQGYGSTGGYGSSQSSQSSYGQQSSYPGY GQQPAPSSTSGSYGSSSQSSSYGQPQSGSYSQQPSYGGQQQSYGQQQSYN PPQGYGQQNQYNSSSGGGGGGGGGGNYGQDQSSMSSGGGSGGGYGNQDQS GGGGSGGYGQQDRGGRGRGGSGGGGGGGGGGYNRSSGGYEPRGRGGGRGG RGGMGGSDRGGFNKFGGSGQIQLWQFLLELLSDSSNSSCITWEGTNGEFK MTDPDEVARRWGERKSKPNMNYDKLSRALRYYYDKNIMTKVHGKRYAYKF DFHGIAQALQPHPPESSLYKYPSDLPYMGSYHAHPQKMNFVAPHPPALPV TSSSFFAAPNPYWNSPTGGIYPNTRLPTSHMPSHLGTYY

The fusion-derived long peptide having the sequence SDRGGFNKFGGSGQIQLWQF (SEQ ID NO: 615) was used for generating neoantigenic peptides (8-11 amino acids) for predicting peptide binding to MHC class I proteins. Results are shown in the Table 7. In the case of acute myeloid leukaemia, patient coverage of the fusion-derived long peptide is about 10%. Recurrent FUS/ERG fusion-derived long peptides are original and placed into the vaccine library.

TABLE 7 FUS/ERG fusion-derived peptides predicted to bind HLA alleles. HLA class I Long peptide spanning neoantigenic peptides alleles that bind fusion breakpoint and  (8-11 amino acids) neoantigens  Fusion yielding neoantigens (SEQ ID NO.) (IC50 <500 nM) FUS/ERG GPPLKKLKQE ATSKSQI MSLW GSGQIQLW (487) HLA-A*24:02 COSF315 GLVSKM KFGGSGQI (488) HLA-A*24:03 (SEQ ID NO.: 486) FGGSGQIQL (489) HLA-B*15:17 GGSGQIQLW (490) HLA-B*39:01 KFGGSGQIQL (491) HLA-B*57:01 KFGGSGQIQLW (492) HLA-B*58:01 NKFGGSGQIQL (493) HLA-C*03:03 HLA-C*14:02

Example 7: Peptides Corresponding to Multiple Gene Fusion Junctions Increase Patient Coverage

FUS/DDIT3 fusions can be found, for example, in myxoid-round cell liposarcoma. The most frequent subtypes of this fusion are formed due to junction of exon 5 of Fus with exon 2 of DDIT3, exon 7 of Fus with exon 2 of DDIT3, and exon 8 of Fus with exon 2 of DDIT3. The amino acid sequences of the FUS/DDIT3 fusion proteins are shown below. In each fusion protein, a stop codon occurs soon after the breakpoint due to a frameshift. Neoantigens predictions were calculated using long peptides having 10 amino acids to the left and all amino acids to the right from the fusion junction.

FUS/DDIT3 (Fus exon 5 to exon 2 of DDIT3) fusion protein (COSF300) (SEQ ID NO.: 494) MASNDYTQQATQSYGAYPTQPGQGYSQQSSQPYGQQSYSGYSQSTDTSGY GQSSYSSYGQSQNTGYGTQSTPQGYGSTGGYGSSQSSQSSYGQQSSYPGY GQQPAPSSTSGSYGSSSQSSSYGQPQSGSYSQQPSYGGQQQSYGQQQSYN PPQGYGQQNQYNSSSGGGGGGGGGVFKKEVYLHTSPHLKAD FUS/DDIT3 (Fus exon 7 to exon 2 of DDIT3) fusion protein (COSF302) (SEQ ID NO.: 495) MASNDYTQQATQSYGAYPTQPGQGYSQQSSQPYGQQSYSGYSQSTDTSGY GQSSYSSYGQSQNTGYGTQSTPQGYGSTGGYGSSQSSQSSYGQQSSYPGY GQQPAPSSTSGSYGSSSQSSSYGQPQSGSYSQQPSYGGQQQSYGQQQSYN PPQGYGQQNQYNSSSGGGGGGGGGGNYGQDQSSMSSGGGSGGGYGNQDQS GGGGSGGYGQQDRGGRGRGGSGGGGGGGGGGYNRSSGGYEPRGRGGGRGG RGGMGGSDRGGFNKFGVFKKEVYLHTSPHLKAD FUS/DDIT3 (Fus exon 8 to exon 2 of DDIT3) fusion protein (COSF301) (SEQ ID NO.: 496) MASNDYTQQATQSYGAYPTQPGQGYSQQSSQPYGQQSYSGYSQSTDTSGY GQSSYSSYGQSQNTGYGTQSTPQGYGSTGGYGSSQSSQSSYGQQSSYPGY GQQPAPSSTSGSYGSSSQSSSYGQPQSGSYSQQPSYGGQQQSYGQQQSYN PPQGYGQQNQYNSSSGGGGGGGGGGNYGQDQSSMSSGGGSGGGYGNQDQS GGGGSGGYGQQDRGGRGRGGSGGGGGGGGGGYNRSSGGYEPRGRGGGRGG RGGMGGSDRGGFNKFGGPRDQGSRHDSVFKKEVYLHTSPHLKAD

Fusion-derived long peptides that were used for generating neoantigenic peptides having 8-11 amino acids for predicting peptide binding to MHC class I are shown in Table 8. Patient coverage with three fusion-derived long peptides is around 50% for myxoid-round cell liposarcoma. Recurrent FUS/DDIT3 fusion-derived peptides spanning fusion breakpoints are original and placed into vaccine library.

TABLE 8 FUS/DDIT3 fusion-derived peptides predicted to bind HLA alleles. Long peptide spanning fusion breakpoint and neoantigens peptides HLA class I alleles that bind Fusion yielding neoantigens (8-11 amino acids) neoantigens (IC50 < 500 nM) FUS/DDIT3 SGGGGGGGGGVFK HTSPHLKA (498) HLA-A*02:01, HLA-A*02:02, COSF300 KEVYLHTSPHLKAD KEVYLHTS (499) HLA-A*02:03, HLA-A*02:06, (SEQ ID NO.: 497) VFKKEVYL (500) HLA-A*02:11, HLA-A*02:17, VYLHTSPH (501) HLA-A*03:01, HLA-A*11:01, YLHTSPHL (502) HLA-A*23:01, HLA-A*24:02, EVYLHTSPH (503) HLA-A*24:03, HLA-A*26:01, GVFKKEVYL (504) HLA-A*29:02, HLA-A*30:01, KEVYLHTSP (505) HLA-A*33:01, HLA-A*66:01, VYLHTSPHL (506) HLA-A*68:01, HLA-A*68:02, YLHTSPHLK (507) HLA-A*69:01, HLA-B*15:01, EVYLHTSPHL (508) HLA-B*15:03, HLA-B*15:03, YLHTSPHLKA (509) HLA-B*40:01, HLA-B*40:02, EVYLHTSPHLK (510) HLA-B*44:03, HLA-B*45:01, KEVYLHTSPHL (511) HLA-C*03:03, HLA-C*12:03, GVFKKEVY (512) HLA-C*14:02 FUS/DDIT3 SDRGGENKFGVEKK FNKFGVFK (514) HLA-A*02:01, HLA-A*02:02, COSF302 EVYLHTSPHLKAD GFNKFGVF (515) HLA-A*02:03, HLA-A*02:06, (SEQ ID NO.: 513) GVFKKEVY (516) HLA-A*02:11, HLA-A*02:17, HTSPHLKA (517) HLA-A*03:01, HLA-A*11:01, KEVYLHTS (518) HLA-A*23:01, HLA-A*24:02, NKFGVFKK (519) HLA-A*24:03, HLA-A*26:01, VFKKEVYL (520) HLA-A*29:02, HLA-A*30:01, VYLHTSPH (521) HLA-A*31:01, HLA-A*33:01, YLHTSPHL (522) HLA-A*66:01, HLA-A*68:01, EVYLHTSPH (523) HLA-A*68:02, HLA-A*69:01, FNKFGVFKK (524) HLA-B*15:01, HLA-B*15:03, GFNKFGVFK (525) HLA-B*40:01, HLA-B*40:02, GGFNKFGVF (526) HLA-B*44:03, HLA-B*45:01, GVFKKEVYL (527) HLA-C*03:03, HLA-C*12:03, KEVYLHTSP (528) HLA-C*14:02 VYLHTSPHL (529) YLHTSPHLK (530) EVYLHTSPHL (531) FGVFKKEVYL (532) GFNKFGVFKK (533) YLHTSPHLKA (534) EVYLHTSPHLK (535) FNKFGVFKKEV (536) GGFNKFGVFKK (537) KEVYLHTSPHL (538) KFGVFKKEVYL (539) NKFGVFKKEVY (540) RGGFNKFGVFK (541) FUS/DDIT3 PRDQGSRHDSVFKK DSVFKKEV (543) HLA-A*02:01, HLA-A*02:02, COSF301 EVYLHTSPHLKAD GSRHDSVF (544) HLA-A*02:03, HLA-A*02:06, (SEQ ID NO.: 542) HTSPHLKA (545) HLA-A*02:11, HLA-A*02:17, KEVYLHTS (546) HLA-A*03:01, HLA-A*11:01, SRHDSVFK (547) HLA-A*23:01, HLA-A*24:02, SVFKKEVY (548) HLA-A*24:03, HLA-A*26:01, VFKKEVYL (549) HLA-A*29:02, HLA-A*30:01, VYLHTSPH (550) HLA-A*33:01, HLA-A*66:01, YLHTSPHL (551) HLA-A*68:01, HLA-A*68:02, EVYLHTSPH (552) HLA-A*69:01, HLA-B*15:01, GSRHDSVFK (553) HLA-B*15:03, HLA-B*15:17, KEVYLHTSP (554) HLA-B*27:05, HLA-B*40:01, QGSRHDSVF (555) HLA-B*40:02, HLA-B*44:03, SRHDSVFKK (556) HLA-B*45:01, HLA-C*03:03, SVFKKEVYL (557) HLA-C*06:02, HLA-C*07:01, VYLHTSPHL (558) HLA-C*12:03, HLA-C*14:02, YLHTSPHLK (559) HLA-C*15:02 DQGSRHDSVF (560) EVYLHTSPHL (561) GSRHDSVFKK (562) RHDSVFKKEV (563) YLHTSPHLKA (564) EVYLHTSPHLK (565) KEVYLHTSPHL (566) RDQGSRHDSVF (567) SRHDSVFKKEV (568)

Example 8: Identification of Novel Peptides in Previously Studied Gene Fusion (BCR/ABL1)

While the BCR/ABL1 fusion and its immunogenic properties have been described, the most comprehensive neoantigens were discovered by the disclosed method, namely two fusion peptides that are present in 68% of patients (FIG. 4). In this non-limiting example, the method described in the specification is applied to identification of BCR/ABL1 fusion peptides for the treatment of CML. Three breakpoints in BCR and ABL1 genes are marked with arrows in FIG. 4. Fusion at these breakpoints yields two BCR/ABL1 gene fusions that are present in 90% of CML patients which comprises 45,000 patients in the U.S. and 950,00 patients worldwide (2). The method discloses two BCR/ABL1 fusion peptides selected based on allele coverage and patient coverage that are present in 68% of CML patients which means that 30,000 patients in the U.S. and 650,000 patients worldwide are eligible for treatment with a cancer vaccine comprising these two peptides shown in FIG. 4. The sequences correspond to SEQ ID NOs: 610 to 611 from top to bottom, respectively.

The COSMIC database contains over 18 exonic variants of the BCR/ABL1 fusion that were analyzed and yielded neoantigen peptides. Half of the fusion exonic variants yielded peptides that were not previously published. According to COSMIC, the fusion variants are found in CML and ALL (including T-ALL and B-ALL).

TABLE 9 BCR/ABL1 fusion-derived peptides predicted to bind HLA alleles. Long peptide spanning fusion Population breakpoint and yielding neoantigens HLA class I alleles that bind covered by (number of neoantigens) neoantigens (IC50 <500 nM) the alleles ASEETYLSHLEALLLKPFSGQ (6) A*03:01, A*11:01, A*23:01, A*24:03, 79% (SEQ ID NO.: 569) A*30:01, A*68:01, B*15:01, B*15:03, B*18:01, B*35:01, B*40:01, B*40:02, B*44:02, B*44:03, C*14:02 EITPRRQSMTVKKGEKPFSGQ (6) A*11:01, A*68:01, B*15:01, B*15:03, 37% (SEQ ID NO.: 570) B*15:17, C*03:03, C*14:02 EITPRRQSMTVKKGESYTFLISSDY A*23:01, A*25:01, A*26:01, A*29:02, 77% ERAEW (17) A*30:01, A*30:02, A*32:01, A*68:01, (SEQ ID NO.: 571) B*15:01, B*15:03, B*15:17, B*35:01, B*40:01, B*40:02, B*44:02, B*44:03, B*45:01, B*57:01, B*58:01, C*03:03 GVATDIQALKAAFDVKALQRPVAS A*02:02, A*02:03, A*02:11, A*03:01, 64% DFEPQG (14) A*11:01, A*30:01, A*31:01, A*68:01, (SEQ ID NO.: 572) A*68:02, B*15:01, B*15:03, B*15:17, B*39:01, B*58:01, C*03:03, C*12:03 GVATDIQALKAAFDVRPSPCEDRH A*31:01, A*68:01, B*15:01, B*15:03, 88% WPGLAL (15) B*15:09, B*15:17, B*35:01, B*38:01, (SEQ ID NO.: 573) B*39:01, B*40:01, B*40:02, B*42:01, B*48:01, B*53:01, B*58:01, C*03:03, C*06:02, C*07:01, C*07:02, C*12:03, C*14:02 KLQTVHSIPLTINKEAGSIEALQRPV A*02:11, A*02:17, A*11:01, A*68:01, 53% ASDF (14) A*68:02, B*15:03, B*15:17, B*35:01, (SEQ ID NO.: 574) B*39:01, B*40:01, B*40:02, B*42:01, B*45:01, C*03:03, C*12:03, C*15:02 KLQTVHSIPLTINKEEALQRPVASD A*31:01, A*68:01, B*07:02, B*15:17, 64% FEPQG (11) B*35:01, B*40:02, B*42:01, B*44:02, (SEQ ID NO.: 575) B*45:01, C*03:03, C*14:02 KLQTVHSIPLTINKEGEKLRVLGYN A*11:01, A*31:01, A*68:01, B*15:17, 54% HNGEW (10) B*40:02, B*44:02, B*44:03, C*03:03, (SEQ ID NO.: 576) C*15:02 KTRVYRDTAEPNWNEKPFSGQ (5) A*68:01, B*15:03, B*35:01, B*42:01, 32% (SEQ ID NO.: 577) B*53:01, C*03:03, C*12:03 KTRVYRDTAEPNWNELDPQALQD A*68:02, A*69:01, B*39:01, B*40:01, 45% RDWQRTV (5) B*40:02, B*44:02, C*03:03, C*12:03 (SEQ ID NO.: 578) LNVIVHSATGFKQSSKALQRPVAS A*02:11, A*03:01, A*11:01, A*30:01, 63% DFEPQG (17) A*31:01, A*68:01, A*68:02, B*15:03, (SEQ ID NO.: 579) B*15:09, B*15:17, B*39:01, B*58:01, C*03:03, C*12:03, C*14:02, C*15:02 LNVIVHSATGFKQSSSEKLRVLGY A*01:01, A*11:01, A*30:01, A*31:01, 88% NHNGEW (18) A*68:01, B*15:01, B*15:03, B*15:09, (SEQ ID NO.: 580) B*15:17, B*18:01, B*39:01, B*44:02, B*44:03, C*03:03, C*06:02, C*07:01, C*15:02 QIWPNDGEGAFHGDAEALQRPVAS A*24:03, A*68:02, B*15:09, B*35:01, 88% DFEPQG (11) B*38:01, B*39:01, B*40:01, B*40:02, (SEQ ID NO.: 581) B*44:02, B*45:01, C*03:03, C*06:02, C*07:01, C*07:02, C*12:03, C*14:02 QIWPNDGEGAFHGDAGEKLRVLG A*24:03, B*15:09, B*15:17, B*38:01, 74% YNHNGEW (7) B*39:01, B*44:02, B*44:03, C*03:03, (SEQ ID NO.: 582) C*06:02, C*07:01, C*12:03, C*14:02 QWSHQQRVGDLFQKLNLRARSNK A*02:06, A*02:11, A*03:01, A*11:01, 50% DAKDPTT (8) A*30:01, A*31:01, A*33:01, A*68:01, (SEQ ID NO.: 583) B*15:03 RKQTGVFGVKIAVVTKSPSAASSI A*02:03, A*02:06, A*11:01, A*30:01, 41% (10) A*31:01, B*15:03, B*15:17, B*39:01, (SEQ ID NO.: 584) C*03:03, C*12:03, C*14:02, C*15:02 SNKDAKDPTTKNSLEKALQRPVAS A*02:02, A*02:03, A*02:11, A*03:01, 68% DFEPQG (10) A*11:01, A*30:01, A*68:01, A*69:01, (SEQ ID NO.: 585) B*15:03, B*15:17, B*39:01, B*40:02, B*44:02, B*58:01, C*03:03, C*12:03, C*14:02, C*15:02 SRDALVSGALESTKATKAKPFSGQ A*03:01, A*11:01, A*30:01, A*31:01, 63% (SEQ ID NO.: 586) A*68:01, B*15:01, B*15:03, B*15:17, B*57:01, B*58:01, C*03:03, C*14:02

Example 9: Method Validation Using EWSR1/FLI1 Gene Fusion

The EWSR1/FLI1 fusion can be found, for example, in Ewing's sarcoma. Two most frequent types of EWSR1/FLI1 fusions occur due to junction of exon 7 of the EWSR1 gene with exon 5 or exon 6 of the FLI1 gene. The amino acid sequences of the fusion proteins are shown below.

Fusion-derived peptides having 8-10 amino acids corresponding to the fusion junction were used for predicting peptide binding to MHC class I proteins. Results are shown in Table 10. Some of the immunogenic EWSR1/FLI1 derived peptides were previously disclosed by patent application U.S. Pat. No. 5,997,869A and were also successfully discovered using methods described herein.

EWSR1/FLI1 (EWSR1 exon 7 to exon 6 of FLI1) fusion protein (COSF166) (SEQ ID NO.: 587) MASTDYSTYSQAAAQQGYSAYTAQPTQGYAQTTQAYGQQSYGTYGQPTDV SYTQAQTTATYGQTAYATSYGQPPTGYTTPTAPQAYSQPVQGYGTGAYDT TTATVTTTQASYAAQSAYGTQPAYPAYGQQPAATAPTRPQDGNKPTETSQ PQSSTGGYNQPSLGYGQSNYSYPQVPGSYPMQPVTAPPSYPPTSYSSTQP TSYDQSSYSQQNTYGQPSSYGQQSSYGQQSSYGQQPPTSYPPQTGSYSQA PSQYSQQSSSYGQQNPSYDSVRRGAWGNNMNSGLNKSPPLGGAQTISKNT EQRPQPDPYQILGPTSSRLANPGSGQIQLWQFLLELLSDSANASCITWEG TNGEFKMTDPDEVARRWGERKSKPNMNYDKLSRALRYYYDKNIMTKVHGK RYAYKFDFHGIAQALQPHPTESSMYKYPSDISYMPSYHAHQQKVNFVPPH PSSMPVTSSSFFGAASQYWTSPTGGIYPNPNVPRHPNTHVPSHLGSYY EWSR1/FLI1 (EWSR1 exon 7 to exon 5 of FLI1) fusion protein (COSF168) (SEQ ID NO.: 588) MASTDYSTYSQAAAQQGYSAYTAQPTQGYAQTTQAYGQQSYGTYGQPTDV SYTQAQTTATYGQTAYATSYGQPPTGYTTPTAPQAYSQPVQGYGTGAYDT TTATVTTTQASYAAQSAYGTQPAYPAYGQQPAATAPTRPQDGNKPTETSQ PQSSTGGYNQPSLGYGQSNYSYPQVPGSYPMQPVTAPPSYPPTSYSSTQP TSYDQSSYSQQNTYGQPSSYGQQSSYGQQSSYGQQPPTSYPPQTGSYSQA PSQYSQQSSSYGQQSSLLAYNTTSHTDQSSRLSVKEDPSYDSVRRGAWGN NMNSGLNKSPPLGGAQTISKNTEQRPQPDPYQILGPTSSRLANPGSGQIQ LWQFLLELLSDSANASCITWEGTNGEFKMTDPDEVARRWGERKSKPNMNY DKLSRALRYYYDKNIMTKVHGKRYAYKFDFHGIAQALQPHPTESSMYKYP SDISYMPSYHAHQQKVNFVPPHPSSMPVTSSSFFGAASQYWTSPTGGIYP NPNVPRHPNTHVPSHLGSYY

TABLE 10 EWSR1/FLI1 fusion-derived peptides predicted to bind HLA alleles. Long peptide spanning HLA class I alleles fusion breakpoint and 8-11-mer neo- that bind neoantigens Fusion yielding neoantigens antigenic peptides (IC50 < 500 nM) EWSR1/FLI1 SQQSSSYGQQNPSYDSVRRG SSYGQQNPSY (591) HLA-A*11:01 COSF166 (SEQ ID NO.: 589) SYGQQNPSY (592) HLA-A*29:02 SSYGQQNPSY (593) HLA-A*31:01 YGQQNPSY (594) HLA-A*68:01 NPSYDSVR (595) HLA-B*15:01 QQNPSYDSV (596) HLA-B*35:01 NPSYDSVRR (597) HLA-C*12:03 YGQQNPSY (598) QQNPSYDSVR (599) EWSR1/FLI1 SQQSSSYGQQSSLLAYNTTS GQQSSLLAY (600) HLA-A*24:02 COSF168 (SEQ ID NO.: 590) QQSSLLAY (601) HLA-A*29:02 SSSYGQQSSL (602) HLA-B*15:01 SSYGQQSSL (603) HLA-B*35:01 SSYGQQSSL (604) HLA-C*03:03 SSYGQQSSLL (605) HLA-C*06:02 SYGQQSSL (606) HLA-C*07:01 SYGQQSSLL (607) HLA-C*07:02 YGQQSSLL (608) YGQQSSLLAY (609)

Other Embodiments

All of the features disclosed in this specification may be combined in any combination. Each feature disclosed in this specification may be replaced by an alternative feature serving the same, equivalent, or similar purpose. Thus, unless expressly stated otherwise, each feature disclosed is only an example of a generic series of equivalent or similar features.

From the above description, one skilled in the art can easily ascertain the essential characteristics of the present disclosure, and without departing from the spirit and scope thereof, can make various changes and modifications of the disclosure to adapt it to various usages and conditions. Thus, other embodiments are also within the claims.

EQUIVALENTS

While several inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

All references, patents and patent applications disclosed herein are incorporated by reference with respect to the subject matter for which each is cited, which in some cases may encompass the entirety of the document.

The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”

The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of.” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. It should be appreciated that embodiments described in this document using an open-ended transitional phrase (e.g., “comprising”) are also contemplated, in alternative embodiments, as “consisting of” and “consisting essentially of” the feature described by the open-ended transitional phrase. For example, if the disclosure describes “a composition comprising A and B”, the disclosure also contemplates the alternative embodiments “a composition consisting of A and B” and “a composition consisting essentially of A and B”. 

What is claimed is:
 1. A method for constructing a therapeutic fusion-specific vaccine library for a cancer patient, the method comprising: a) identifying one or more tumor-specific gene fusions from patient data; b) identifying one or more fusion-derived neoantigens, wherein the fusion-derived neoantigen comprises amino acid sequences corresponding to one or more tumor-specific gene fusions; c) obtaining information relating to interaction between fusion-derived neoantigens with one or more HLA alleles; and d) selecting at least one fusion-derived neoantigen for the therapeutic fusion-specific vaccine library.
 2. A method of selecting a therapeutic fusion-specific vaccine for a cancer patient, the method comprising: a) determining the presence of one or more tumor-specific gene fusions in a biological sample from the cancer patient; b) obtaining information relating to one or more HLA alleles of the cancer patient; c) analyzing a library of fusion-specific vaccines, wherein each fusion-specific vaccine in the library comprises one or more fusion-derived neoantigens having a nucleic acid sequence and/or an amino acid sequence corresponding to one or more tumor-specific gene fusions; and d) selecting at least one fusion-specific vaccine in the library as the therapeutic fusion-specific vaccine for the cancer patient by selecting the fusion-specific vaccine comprising one or more fusion-derived neoantigens that i) correspond to one or more tumor-specific gene fusions of the cancer patient, and ii) bind one or more HLA alleles of the cancer patient.
 3. A method of constructing a de novo therapeutic fusion-specific vaccine for a cancer patient, the method comprising: a) determining the presence of one or more tumor-specific gene fusions in a biological sample from the cancer patient; b) obtaining information relating to one or more HLA alleles of the cancer patient; c) constructing at least one fusion-specific vaccine as the de novo therapeutic fusion-specific vaccine for the cancer patient by constructing the fusion-specific vaccine comprising one or more fusion-derived neoantigens that i) correspond to one or more tumor-specific gene fusions of the cancer patient, and ii) bind one or more HLA alleles of the cancer patient.
 4. The method of any one of the foregoing, further comprising administering the therapeutic fusion-specific vaccine to the cancer patient.
 5. The method of claim 2 or 3, wherein the biological sample is a tissue sample or fluid sample taken from the cancer patient.
 6. The method of claim 2 or 3, wherein the biological sample is analyzed by DNA sequencing, RNA sequencing, and/or protein sequencing.
 7. The method of claim 2 or 3, wherein one or more tumor-specific gene fusions are identified in the biological sample.
 8. The method of any one of the foregoing claims, wherein information relating to one or more HLA alleles of the cancer patient are obtained by analysis of the biological sample.
 9. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more nucleic acid sequences corresponding to one or more tumor-specific gene fusions.
 10. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having amino acid sequences corresponding to one or more tumor-specific gene fusions.
 11. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides selected from Table A.
 12. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 peptides corresponding to one or more tumor-specific gene fusions.
 13. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises 20 or more peptides corresponding to one or more tumor-specific gene fusions.
 14. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC50 less than 500 nM.
 15. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC50 less than 250 nM.
 16. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC50 less than 100 nM.
 17. The method of any one of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides that bind to one or more HLA alleles of the cancer patient with an IC50 less than 50 nM.
 18. The method of any of the foregoing claims, wherein the library of fusion-specific vaccines comprises at least 2-10 fusion-specific vaccines corresponding to distinct fusion-derived neoantigens.
 19. The method of any of the foregoing claims, wherein the library of fusion-specific vaccines comprises at least 5-10 fusion-specific vaccines corresponding to distinct fusion-derived neoantigens.
 20. The method of any of the foregoing claims, wherein the library of fusion-specific vaccines comprises at least 10-50 fusion-specific vaccines corresponding to distinct fusion-derived neoantigens.
 21. The method of any of the foregoing claims, wherein the library of fusion-specific vaccines comprises at least 50-100 fusion-specific vaccines corresponding to distinct fusion-derived neoantigens.
 22. The method of any of the foregoing claims, wherein the library of fusion-specific vaccines comprises 100 or more fusion-specific vaccines corresponding to distinct fusion-derived neoantigens.
 23. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having 8-10 amino acids.
 24. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having 10-25 amino acids.
 25. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having 25-50 amino acids.
 26. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having 50-100 amino acids.
 27. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having 100 or more amino acids.
 28. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having an amino acid sequence corresponding to a one or more tumor-specific gene fusions and one or more addition amino acid sequences.
 29. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises two or more peptides having an amino acid sequence corresponding to two or more tumor-specific gene fusions and one or more addition amino acid sequences.
 30. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more peptides having a modification.
 31. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises one or more adjuvants.
 32. The method of any of the foregoing claims, wherein the fusion-specific vaccine comprises the peptide having a concentration of 100 ng-10 mg.
 33. The method of any of the foregoing claims, wherein the fusion-specific vaccine is administered once to the cancer patient.
 34. The method of any of the foregoing claims, wherein the cancer patient is treated with two or more doses of the fusion-specific vaccine.
 35. The method of any one of the foregoing claims, wherein the library of fusion-specific vaccines comprises fusion-derived neoantigens corresponding to gene fusions that are present in a type of cancer.
 36. The method of any one of the foregoing claims, wherein the type of cancer is melanoma, skin cancer, head and neck cancer, breast cancer, lung cancer, ovarian cancer, cervical cancer, prostate cancer, thyroid cancer, kidney cancer, liver cancer, pancreatic cancer, gastric cancer, testicular cancer, brain tumor, glioma, glioblastoma, solitary fibrous tumor, bladder cancer, colorectal cancer, renal cell carcinoma, sarcoma, myeloma, leukemia, and/or lymphoma.
 37. The method of any one of the foregoing claims, wherein the type of cancer is a metastatic tumor.
 38. The method of any one of the foregoing claims, wherein the type of cancer is any tumor type.
 39. The method of any one of the foregoing claims, wherein the cancer patient is administered dendritic cells or other antigen presenting cells that have been pulsed with at least one fusion-derived neoantigens from the fusion-specific vaccine library.
 40. The method of any one of the foregoing claims, wherein autologous T-cells can be collected from the cancer patient, stimulated ex vivo with fusion-derived neoantigens, and stimulated autologous T-cells are transfused into the cancer patient.
 41. The method of any one of the foregoing claims, wherein one or more fusion-specific vaccines are DNA or RNA molecules that encode fusion-derived neoantigens.
 42. The method of any one of the foregoing claims, wherein the cancer patient is administered dendritic cells or other antigen presenting cells comprising at least one fusion-derived neoantigens from the fusion-specific vaccine library. 